{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "53eb9948",
   "metadata": {},
   "source": [
    "#### 多因子03因子预处理-20231016-大小盘因子预处理-风格因子\n",
    "\n",
    "20231016-如何计算大小盘因子<br>\n",
    "https://www.bilibili.com/video/BV1vu411N7fn/"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc287599",
   "metadata": {},
   "source": [
    "## 因子预处理\n",
    "\n",
    "https://www.wolai.com/stupidccl/3QzCwVcyRScvSt9nUugzQG"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89c4e56c",
   "metadata": {},
   "source": [
    "在因子预处理中，概念和定义有点多，强行解释有点费力，比如中性化、标准化等等。但是只要用一下，就很容易弄懂。\n",
    "\n",
    "因此，本部分通过几个案例来带大家实际上手，轻松掌握因子预处理。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a7b4335",
   "metadata": {},
   "source": [
    "## 大小盘因子预处理-风格因子\n",
    "\n",
    "https://www.bilibili.com/video/BV1vu411N7fn?t=0.3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30fc2d55",
   "metadata": {},
   "source": [
    "### 什么是大小盘因子？\n",
    "\n",
    "大小盘因子应该是所有因子中最容易理解的一个，尤其是在我国的资本市场上。\n",
    "\n",
    "对我国股市有一点了解的投资者都知道，股民们经常会说“这个股票盘子太大，涨起不来”。这里的“盘子大”指的就是股票的市值大。"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "d3d00a51",
   "metadata": {},
   "source": [
    "#### 如何判断大小盘走势？\n",
    "\n",
    "上证50和中证500这两个指数背后的个股行业的分布差异很大，但是市值是这两个指数最显著的差异。<br>\n",
    "通常我们会用这两个指数之间的关系来判断市场上大小盘股票走势的相对强弱。<br>\n",
    "![image.png](attachment:image.png)\n",
    "有的时候中证500走势会比上证50的走势强势，有的时候则是上证50的走势更加强势一些。<br>\n",
    "例如在2009—2011年，中证500的上涨幅度明显超过上证50；<br>\n",
    "再比如2011—2013年，这个时间段上证50下跌较少，而中证500则有较大幅度的下跌。<br>\n",
    "由此我们可以发现，市值的大小对股票的涨跌是有较大影响的，这也是为什么会有“盘子太大，涨不起来”这一说法的原因。<br>\n",
    "从整体上来看，在A股过去的历史中，中证500代表的中小市值股票是跑赢上证50代表的大市值股票的，也就是投资者更加偏好小市值股票。<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e22d8a5",
   "metadata": {},
   "source": [
    "#### <font color=\"#FF0000\">为什么韭菜偏爱小市值？</font>  \n",
    "\n",
    "从经济逻辑上来讲，对于小市值公司能够获得超额收益这个现象有以下3个原因。\n",
    "\n",
    "1. 小市值的公司往往是新兴企业，未来经营具有很大的**不确定性**，所以投资者投资小市值的公司需要获得相应的**风险溢价**，故小市值公司的股票表现会好于大盘股\n",
    "2. 我国股市的投资者炒作情绪较浓重，在一个不能做空的市场，往往**炒作**情绪越浓重的板块越容易产生超额收益。由于小盘股往往是炒作的对象，因此小市值公司股票表现会有好于大盘股的表现。\n",
    "3. 小市值的公司往往都是轻资产的公司，**成长性较好**。在我国这样一个增速较快的经济体中，这一类公司往往具有更好的前景，从而其股价涨幅较好。"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "ddf6484f",
   "metadata": {},
   "source": [
    "### 如何计算大小盘因子？\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae9bfb32",
   "metadata": {},
   "source": [
    "**公式**\n",
    "\n",
    "$$\n",
    "上市公司的市值大小=上市公司发行总股本×A股市场股票价格\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c874b17e",
   "metadata": {},
   "source": [
    "#### 上市公司市值分布情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdc51d25",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import pandas as pd\n",
    "# import numpy as np\n",
    "# import matplotlib.pyplot as plt\n",
    "# import warnings\n",
    "# warnings.simplefilter(action=\"ignore\", category=Warning)\n",
    "\n",
    "# trading_data_2019 = pd.read_csv('factors/data/2019_trading_data.csv')\n",
    "# sub_trading_data = trading_data_2019.query(\"data_date=='2019-05-27'\")\n",
    "# sub_trading_data['mv'].hist(bins=100, figsize=(18, 9))\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "eea64af2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.simplefilter(action=\"ignore\", category=Warning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a3630f23",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data_date</th>\n",
       "      <th>secucode</th>\n",
       "      <th>daily_return</th>\n",
       "      <th>mv</th>\n",
       "      <th>free_mv</th>\n",
       "      <th>turnover</th>\n",
       "      <th>ind_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-02</td>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>-0.020256</td>\n",
       "      <td>1.577961e+07</td>\n",
       "      <td>1.577946e+07</td>\n",
       "      <td>0.003418</td>\n",
       "      <td>480000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-02</td>\n",
       "      <td>000002.SZ</td>\n",
       "      <td>0.003359</td>\n",
       "      <td>2.324083e+07</td>\n",
       "      <td>2.321926e+07</td>\n",
       "      <td>0.001064</td>\n",
       "      <td>430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-02</td>\n",
       "      <td>000004.SZ</td>\n",
       "      <td>0.001871</td>\n",
       "      <td>1.348666e+05</td>\n",
       "      <td>1.333192e+05</td>\n",
       "      <td>0.001068</td>\n",
       "      <td>370000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-02</td>\n",
       "      <td>000005.SZ</td>\n",
       "      <td>-0.003731</td>\n",
       "      <td>2.826293e+05</td>\n",
       "      <td>2.824716e+05</td>\n",
       "      <td>0.010301</td>\n",
       "      <td>410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-02</td>\n",
       "      <td>000006.SZ</td>\n",
       "      <td>-0.005792</td>\n",
       "      <td>6.952474e+05</td>\n",
       "      <td>6.943786e+05</td>\n",
       "      <td>0.009106</td>\n",
       "      <td>430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696826</th>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>603993.SH</td>\n",
       "      <td>-0.004566</td>\n",
       "      <td>9.417269e+06</td>\n",
       "      <td>7.702277e+06</td>\n",
       "      <td>0.026575</td>\n",
       "      <td>240000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696827</th>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>603996.SH</td>\n",
       "      <td>-0.015656</td>\n",
       "      <td>1.509755e+05</td>\n",
       "      <td>1.509755e+05</td>\n",
       "      <td>0.047197</td>\n",
       "      <td>270000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696828</th>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>603997.SH</td>\n",
       "      <td>-0.009804</td>\n",
       "      <td>8.270712e+05</td>\n",
       "      <td>8.270712e+05</td>\n",
       "      <td>0.003506</td>\n",
       "      <td>280000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696829</th>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>603998.SH</td>\n",
       "      <td>0.023428</td>\n",
       "      <td>3.605991e+05</td>\n",
       "      <td>3.605991e+05</td>\n",
       "      <td>0.055506</td>\n",
       "      <td>370000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696830</th>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>603999.SH</td>\n",
       "      <td>-0.027815</td>\n",
       "      <td>4.227840e+05</td>\n",
       "      <td>4.227840e+05</td>\n",
       "      <td>0.030791</td>\n",
       "      <td>720000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>696831 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         data_date   secucode  daily_return            mv       free_mv  \\\n",
       "0       2019-01-02  000001.SZ     -0.020256  1.577961e+07  1.577946e+07   \n",
       "1       2019-01-02  000002.SZ      0.003359  2.324083e+07  2.321926e+07   \n",
       "2       2019-01-02  000004.SZ      0.001871  1.348666e+05  1.333192e+05   \n",
       "3       2019-01-02  000005.SZ     -0.003731  2.826293e+05  2.824716e+05   \n",
       "4       2019-01-02  000006.SZ     -0.005792  6.952474e+05  6.943786e+05   \n",
       "...            ...        ...           ...           ...           ...   \n",
       "696826  2019-12-31  603993.SH     -0.004566  9.417269e+06  7.702277e+06   \n",
       "696827  2019-12-31  603996.SH     -0.015656  1.509755e+05  1.509755e+05   \n",
       "696828  2019-12-31  603997.SH     -0.009804  8.270712e+05  8.270712e+05   \n",
       "696829  2019-12-31  603998.SH      0.023428  3.605991e+05  3.605991e+05   \n",
       "696830  2019-12-31  603999.SH     -0.027815  4.227840e+05  4.227840e+05   \n",
       "\n",
       "        turnover  ind_code  \n",
       "0       0.003418    480000  \n",
       "1       0.001064    430000  \n",
       "2       0.001068    370000  \n",
       "3       0.010301    410000  \n",
       "4       0.009106    430000  \n",
       "...          ...       ...  \n",
       "696826  0.026575    240000  \n",
       "696827  0.047197    270000  \n",
       "696828  0.003506    280000  \n",
       "696829  0.055506    370000  \n",
       "696830  0.030791    720000  \n",
       "\n",
       "[696831 rows x 7 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 上市公司市值分布情况\n",
    "trading_data_2019=pd.read_csv('./data/2019_trading_data.csv')\n",
    "trading_data_2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "99558b12",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data_date</th>\n",
       "      <th>secucode</th>\n",
       "      <th>daily_return</th>\n",
       "      <th>mv</th>\n",
       "      <th>free_mv</th>\n",
       "      <th>turnover</th>\n",
       "      <th>ind_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>334461</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>0.001619</td>\n",
       "      <td>2.123980e+07</td>\n",
       "      <td>2.123960e+07</td>\n",
       "      <td>0.004936</td>\n",
       "      <td>480000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334462</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000002.SZ</td>\n",
       "      <td>0.006711</td>\n",
       "      <td>2.625533e+07</td>\n",
       "      <td>2.623096e+07</td>\n",
       "      <td>0.000961</td>\n",
       "      <td>430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334463</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000004.SZ</td>\n",
       "      <td>0.087059</td>\n",
       "      <td>1.939861e+05</td>\n",
       "      <td>1.915766e+05</td>\n",
       "      <td>0.007673</td>\n",
       "      <td>370000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334464</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000005.SZ</td>\n",
       "      <td>0.019802</td>\n",
       "      <td>3.270879e+05</td>\n",
       "      <td>3.269054e+05</td>\n",
       "      <td>0.014683</td>\n",
       "      <td>410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334465</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000006.SZ</td>\n",
       "      <td>0.045372</td>\n",
       "      <td>7.775971e+05</td>\n",
       "      <td>7.763248e+05</td>\n",
       "      <td>0.020896</td>\n",
       "      <td>430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338036</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603991.SH</td>\n",
       "      <td>0.035249</td>\n",
       "      <td>1.422873e+05</td>\n",
       "      <td>7.841965e+04</td>\n",
       "      <td>0.006144</td>\n",
       "      <td>220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338037</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603993.SH</td>\n",
       "      <td>0.015464</td>\n",
       "      <td>6.960314e+06</td>\n",
       "      <td>6.960314e+06</td>\n",
       "      <td>0.007321</td>\n",
       "      <td>240000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338038</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603997.SH</td>\n",
       "      <td>0.030383</td>\n",
       "      <td>4.987423e+05</td>\n",
       "      <td>4.928593e+05</td>\n",
       "      <td>0.007838</td>\n",
       "      <td>280000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338039</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603998.SH</td>\n",
       "      <td>0.037820</td>\n",
       "      <td>4.073690e+05</td>\n",
       "      <td>3.967085e+05</td>\n",
       "      <td>0.064843</td>\n",
       "      <td>370000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338040</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603999.SH</td>\n",
       "      <td>0.033028</td>\n",
       "      <td>3.242880e+05</td>\n",
       "      <td>3.242880e+05</td>\n",
       "      <td>0.012597</td>\n",
       "      <td>720000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3580 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         data_date   secucode  daily_return            mv       free_mv  \\\n",
       "334461  2019-05-27  000001.SZ      0.001619  2.123980e+07  2.123960e+07   \n",
       "334462  2019-05-27  000002.SZ      0.006711  2.625533e+07  2.623096e+07   \n",
       "334463  2019-05-27  000004.SZ      0.087059  1.939861e+05  1.915766e+05   \n",
       "334464  2019-05-27  000005.SZ      0.019802  3.270879e+05  3.269054e+05   \n",
       "334465  2019-05-27  000006.SZ      0.045372  7.775971e+05  7.763248e+05   \n",
       "...            ...        ...           ...           ...           ...   \n",
       "338036  2019-05-27  603991.SH      0.035249  1.422873e+05  7.841965e+04   \n",
       "338037  2019-05-27  603993.SH      0.015464  6.960314e+06  6.960314e+06   \n",
       "338038  2019-05-27  603997.SH      0.030383  4.987423e+05  4.928593e+05   \n",
       "338039  2019-05-27  603998.SH      0.037820  4.073690e+05  3.967085e+05   \n",
       "338040  2019-05-27  603999.SH      0.033028  3.242880e+05  3.242880e+05   \n",
       "\n",
       "        turnover  ind_code  \n",
       "334461  0.004936    480000  \n",
       "334462  0.000961    430000  \n",
       "334463  0.007673    370000  \n",
       "334464  0.014683    410000  \n",
       "334465  0.020896    430000  \n",
       "...          ...       ...  \n",
       "338036  0.006144    220000  \n",
       "338037  0.007321    240000  \n",
       "338038  0.007838    280000  \n",
       "338039  0.064843    370000  \n",
       "338040  0.012597    720000  \n",
       "\n",
       "[3580 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# trading_data_2019 = pd.read_csv('factors/data/2019_trading_data.csv')\n",
    "sub_trading_data = trading_data_2019.query(\"data_date=='2019-05-27'\")\n",
    "sub_trading_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6cf7790c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABBsAAAIVCAYAAACQmPeOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3dfYyl5Xnf8d9lcAk18VuJVxRIQSl5wXZMypbQplGHOC3Erooj1dK6liGJq01cEiUqUoOjqk5rIVGpJK2dQLKJLXBDvaKJU2htp3Fppk4UCIbU8RoI9cpQvAFBHTu2143cLL76xzzIUzLMHGbvndl55vORRnPmPs855z577S6H756X6u4AAAAAjPKC7d4AAAAAMC9iAwAAADCU2AAAAAAMJTYAAAAAQ4kNAAAAwFBiAwAAADDUqdu9gY2ceeaZfd555233Np6XL3/5y3nRi1603dvgBDHfeTPfeTPfeTPfeTPfeTPf+TLbebv//vs/293fsNZ5J31sOO+883Lfffdt9zael+Xl5SwtLW33NjhBzHfezHfezHfezHfezHfezHe+zHbequp/Pdd5XkYBAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAENtGBuq6uuq6t6q+oOqeqCq/sW0/vKq+khVfWr6/rJVl3l7VR2uqoer6vJV6xdX1aHpvHdVVZ2YuwUAAABsl0We2fCVJN/T3a9JclGSK6rq0iTXJbmruy9Ictf0c6rqwiT7krwyyRVJbqqqU6brujnJ/iQXTF9XDLwvAAAAwElgw9jQK45OP75w+uokVya5dVq/NckbptNXJjnY3V/p7keSHE5ySVWdleTF3X13d3eS9626DAAAADATpy5y0PTMhPuT/NUkP9/dv1dVe7r7iSTp7ieq6hXT4WcnuWfVxY9Ma382nX72+uwc+qMv5Aeu++C6xzx6w+u3aDcAAACwtRaKDd39dJKLquqlSX69ql61zuFrvQ9Dr7P+56+gan9WXm6RPXv2ZHl5eZFtnjT2nJ5c++pj6x6z0+4TX3P06FHzmzHznTfznTfznTfznTfznS+z3b0Wig3P6O4/qarlrLzXwpNVddb0rIazkjw1HXYkybmrLnZOksen9XPWWF/rdg4kOZAke/fu7aWlpeezzW337tvuyI2H1v+lffTNS1uzGYZbXl7OTvs9yeLMd97Md97Md97Md97Md77Mdvda5NMovmF6RkOq6vQk35vkD5PcmeTq6bCrk9wxnb4zyb6qOq2qzs/KG0HeO73k4ktVden0KRRXrboMAAAAMBOLPLPhrCS3Tu/b8IIkt3f3f66qu5PcXlVvTfJYkjcmSXc/UFW3J3kwybEk10wvw0iStyW5JcnpST48fQEAAAAzsmFs6O5PJPmONdb/OMlrn+My1ye5fo31+5Ks934PAAAAwA634csoAAAAAJ4PsQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGCoDWNDVZ1bVb9VVQ9V1QNV9ePT+k9X1R9V1cenr9etuszbq+pwVT1cVZevWr+4qg5N572rqurE3C0AAABgu5y6wDHHklzb3b9fVV+f5P6q+sh03s92979efXBVXZhkX5JXJvnLSf5rVX1zdz+d5OYk+5Pck+RDSa5I8uExdwUAAAA4GWz4zIbufqK7f386/aUkDyU5e52LXJnkYHd/pbsfSXI4ySVVdVaSF3f33d3dSd6X5A3HfQ8AAACAk0qt/H//ggdXnZfko0leleSfJPmBJF9Mcl9Wnv3w+ar6uST3dPevTJd5T1aevfBokhu6+3un9e9O8pPd/ffWuJ39WXkGRPbs2XPxwYMHN3fvtslTn/tCnvzT9Y959dkv2ZrNMNzRo0dzxhlnbPc2OEHMd97Md97Md97Md97Md77Mdt4uu+yy+7t771rnLfIyiiRJVZ2R5NeS/ER3f7Gqbk7yziQ9fb8xyQ8lWet9GHqd9T+/2H0gyYEk2bt3by8tLS26zZPCu2+7IzceWv+X9tE3L23NZhhueXk5O+33JIsz33kz33kz33kz33kz3/ky291roU+jqKoXZiU03NbdH0iS7n6yu5/u7q8m+aUkl0yHH0ly7qqLn5Pk8Wn9nDXWAQAAgBlZ5NMoKsl7kjzU3T+zav2sVYd9f5JPTqfvTLKvqk6rqvOTXJDk3u5+IsmXqurS6TqvSnLHoPsBAAAAnCQWeRnFdyV5S5JDVfXxae2nkrypqi7KykshHk3yw0nS3Q9U1e1JHszKJ1lcM30SRZK8LcktSU7Pyvs4+CQKAAAAmJkNY0N3/07Wfr+FD61zmeuTXL/G+n1ZeXNJAAAAYKYWes8GAAAAgEWJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADLVhbKiqc6vqt6rqoap6oKp+fFp/eVV9pKo+NX1/2arLvL2qDlfVw1V1+ar1i6vq0HTeu6qqTszdAgAAALbLIs9sOJbk2u7+tiSXJrmmqi5Mcl2Su7r7giR3TT9nOm9fklcmuSLJTVV1ynRdNyfZn+SC6euKgfcFAAAAOAlsGBu6+4nu/v3p9JeSPJTk7CRXJrl1OuzWJG+YTl+Z5GB3f6W7H0lyOMklVXVWkhd3993d3Unet+oyAAAAwEw8r/dsqKrzknxHkt9Lsqe7n0hWgkSSV0yHnZ3kM6sudmRaO3s6/ex1AAAAYEZOXfTAqjojya8l+Ynu/uI6b7ew1hm9zvpat7U/Ky+3yJ49e7K8vLzoNk8Ke05Prn31sXWP2Wn3ia85evSo+c2Y+c6b+c6b+c6b+c6b+c6X2e5eC8WGqnphVkLDbd39gWn5yao6q7ufmF4i8dS0fiTJuasufk6Sx6f1c9ZY/3O6+0CSA0myd+/eXlpaWuzenCTefdsdufHQ+r+0j755aWs2w3DLy8vZab8nWZz5zpv5zpv5zpv5zpv5zpfZ7l6LfBpFJXlPkoe6+2dWnXVnkqun01cnuWPV+r6qOq2qzs/KG0HeO73U4ktVdel0nVetugwAAAAwE4s8s+G7krwlyaGq+vi09lNJbkhye1W9NcljSd6YJN39QFXdnuTBrHySxTXd/fR0ubcluSXJ6Uk+PH0BAAAAM7JhbOju38na77eQJK99jstcn+T6NdbvS/Kq57NBAAAAYGd5Xp9GAQAAALARsQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGAosQEAAAAYSmwAAAAAhhIbAAAAgKHEBgAAAGCoDWNDVb23qp6qqk+uWvvpqvqjqvr49PW6Vee9vaoOV9XDVXX5qvWLq+rQdN67qqrG3x0AAABguy3yzIZbklyxxvrPdvdF09eHkqSqLkyyL8krp8vcVFWnTMffnGR/kgumr7WuEwAAANjhNowN3f3RJJ9b8PquTHKwu7/S3Y8kOZzkkqo6K8mLu/vu7u4k70vyhs1uGgAAADh5nXocl/3RqroqyX1Jru3uzyc5O8k9q445Mq392XT62etrqqr9WXkWRPbs2ZPl5eXj2ObW23N6cu2rj617zE67T3zN0aNHzW/GzHfezHfezHfezHfezHe+zHb32mxsuDnJO5P09P3GJD+UZK33Yeh11tfU3QeSHEiSvXv39tLS0ia3uT3efdsdufHQ+r+0j755aWs2w3DLy8vZab8nWZz5zpv5zpv5zpv5zpv5zpfZ7l6b+jSK7n6yu5/u7q8m+aUkl0xnHUly7qpDz0ny+LR+zhrrAAAAwMxsKjZM78HwjO9P8swnVdyZZF9VnVZV52fljSDv7e4nknypqi6dPoXiqiR3HMe+AQAAgJPUhi+jqKr3J1lKcmZVHUnyjiRLVXVRVl4K8WiSH06S7n6gqm5P8mCSY0mu6e6np6t6W1Y+2eL0JB+evgAAAICZ2TA2dPeb1lh+zzrHX5/k+jXW70vyque1OwAAAGDH2dTLKAAAAACei9gAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQYgMAAAAwlNgAAAAADCU2AAAAAEOJDQAAAMBQG8aGqnpvVT1VVZ9ctfbyqvpIVX1q+v6yVee9vaoOV9XDVXX5qvWLq+rQdN67qqrG3x0AAABguy3yzIZbklzxrLXrktzV3RckuWv6OVV1YZJ9SV45XeamqjpluszNSfYnuWD6evZ1AgAAADOwYWzo7o8m+dyzlq9Mcut0+tYkb1i1frC7v9LdjyQ5nOSSqjoryYu7++7u7iTvW3UZAAAAYEY2+54Ne7r7iSSZvr9iWj87yWdWHXdkWjt7Ov3sdQAAAGBmTh18fWu9D0Ovs772lVTtz8pLLrJnz54sLy8P2dxW2XN6cu2rj617zE67T3zN0aNHzW/GzHfezHfezHfezHfezHe+zHb32mxseLKqzuruJ6aXSDw1rR9Jcu6q485J8vi0fs4a62vq7gNJDiTJ3r17e2lpaZPb3B7vvu2O3Hho/V/aR9+8tDWbYbjl5eXstN+TLM58581858185818581858tsd6/NvoziziRXT6evTnLHqvV9VXVaVZ2flTeCvHd6qcWXqurS6VMorlp1GQAAAGBGNnxmQ1W9P8lSkjOr6kiSdyS5IcntVfXWJI8leWOSdPcDVXV7kgeTHEtyTXc/PV3V27LyyRanJ/nw9AUAAADMzIaxobvf9BxnvfY5jr8+yfVrrN+X5FXPa3cAAADAjrPZl1EAAAAArElsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGOq4YkNVPVpVh6rq41V137T28qr6SFV9avr+slXHv72qDlfVw1V1+fFuHgAAADj5jHhmw2XdfVF3751+vi7JXd19QZK7pp9TVRcm2ZfklUmuSHJTVZ0y4PYBAACAk8iJeBnFlUlunU7fmuQNq9YPdvdXuvuRJIeTXHICbh8AAADYRtXdm79w1SNJPp+kk/xidx+oqj/p7peuOubz3f2yqvq5JPd0969M6+9J8uHu/tU1rnd/kv1JsmfPnosPHjy46T1uh6c+94U8+afrH/Pqs1+yNZthuKNHj+aMM87Y7m1wgpjvvJnvvJnvvJnvvJnvfJntvF122WX3r3qVw//n1OO87u/q7ser6hVJPlJVf7jOsbXG2pqlo7sPJDmQJHv37u2lpaXj3ObWevdtd+TGQ+v/0j765qWt2QzDLS8vZ6f9nmRx5jtv5jtv5jtv5jtv5jtfZrt7HdfLKLr78en7U0l+PSsvi3iyqs5Kkun7U9PhR5Kcu+ri5yR5/HhuHwAAADj5bDo2VNWLqurrnzmd5O8m+WSSO5NcPR12dZI7ptN3JtlXVadV1flJLkhy72ZvHwAAADg5Hc/LKPYk+fWqeuZ6/n13/0ZVfSzJ7VX11iSPJXljknT3A1V1e5IHkxxLck13P31cuwcAAABOOpuODd396SSvWWP9j5O89jkuc32S6zd7mwAAAMDJ70R89CUAAACwi4kNAAAAwFBiAwAAADCU2AAAAAAMJTYAAAAAQ4kNAAAAwFBiAwAAADCU2AAAAAAMJTYAAAAAQ4kNAAAAwFBiAwAAADCU2AAAAAAMJTYAAAAAQ4kNAAAAwFBiAwAAADCU2AAAAAAMJTYAAAAAQ4kNAAAAwFBiAwAAADCU2AAAAAAMJTYAAAAAQ4kNAAAAwFCnbvcGdqvzrvvgQsc9esPrT/BOAAAAYCzPbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGEhsAAACAocQGAAAAYCixAQAAABhKbAAAAACGOnW7N8D6zrvugxse8+gNr9+CnQAAAMBiPLMBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIYSGwAAAIChxAYAAABgKLEBAAAAGEpsAAAAAIY6dbs3wPE777oPbnjMoze8fgt2AgAAANsQG6rqiiT/NskpSX65u2/Y6j3sRoIEAAAAW2VLY0NVnZLk55P8nSRHknysqu7s7ge3ch+sTZAAAABghK1+ZsMlSQ5396eTpKoOJrkyidiwQywSJBYhWgAAAMzXVseGs5N8ZtXPR5J85xbvgZPAqGiRLBYuRt7eta8+lh9Y5/pG7WfRIDPquk6261nEonMVtwAAYGtVd2/djVW9Mcnl3f2Ppp/fkuSS7v6xZx23P8n+6cdvSfLwlm1yjDOTfHa7N8EJY77zZr7zZr7zZr7zZr7zZr7zZbbz9le6+xvWOmOrn9lwJMm5q34+J8njzz6ouw8kObBVmxqtqu7r7r3bvQ9ODPOdN/OdN/OdN/OdN/OdN/OdL7PdvV6wxbf3sSQXVNX5VfUXkuxLcucW7wEAAAA4gbb0mQ3dfayqfjTJf8nKR1++t7sf2Mo9AAAAACfWVr+MIt39oSQf2urb3WI79iUgLMR85818581858185818581858tsd6ktfYNIAAAAYP62+j0bAAAAgJkTGzapqq6oqoer6nBVXbfG+VVV75rO/0RV/bXt2Cebs8B83zzN9RNV9btV9Zrt2Cebs9F8Vx3316vq6ar6B1u5P47PIvOtqqWq+nhVPVBV/32r98jmLfD380uq6j9V1R9M8/3B7dgnm1NV762qp6rqk89xvsdXO9gC8/X4agfbaL6rjvP4apcQGzahqk5J8vNJvi/JhUneVFUXPuuw70tywfS1P8nNW7pJNm3B+T6S5G9397cneWe8Fm3HWHC+zxz3r7LyhrbsEIvMt6pemuSmJH+/u1+Z5I1bvlE2ZcE/v9ckebC7X5NkKcmN0ydgsTPckuSKdc73+GpnuyXrz9fjq53tlqw/X4+vdhmxYXMuSXK4uz/d3f83ycEkVz7rmCuTvK9X3JPkpVV11lZvlE3ZcL7d/bvd/fnpx3uSnLPFe2TzFvnzmyQ/luTXkjy1lZvjuC0y33+Y5APd/ViSdLcZ7xyLzLeTfH1VVZIzknwuybGt3Sab1d0fzcrMnovHVzvYRvP1+GpnW+DPb+Lx1a4iNmzO2Uk+s+rnI9Pa8z2Gk9Pznd1bk3z4hO6IkTacb1WdneT7k/zCFu6LMRb58/vNSV5WVctVdX9VXbVlu+N4LTLfn0vybUkeT3IoyY9391e3ZntsAY+vdg+Pr2bG46vdZ8s/+nImao21Z3+sxyLHcHJaeHZVdVlW/mP4t07ojhhpkfn+myQ/2d1Pr/zjKDvIIvM9NcnFSV6b5PQkd1fVPd39P0/05jhui8z38iQfT/I9Sb4pyUeq6re7+4snenNsCY+vdgGPr2bL46tdRmzYnCNJzl318zlZ+ReU53sMJ6eFZldV357kl5N8X3f/8RbtjeO3yHz3Jjk4/YfwzCSvq6pj3f0ft2aLHIdF/37+bHd/OcmXq+qjSV6TRGw4+S0y3x9MckOvfLb34ap6JMm3Jrl3a7bICebx1cx5fDVrHl/tMl5GsTkfS3JBVZ0/venUviR3PuuYO5NcNb1r8qVJvtDdT2z1RtmUDedbVd+Y5ANJ3uJfQ3ecDefb3ed393ndfV6SX03yj/2HcMdY5O/nO5J8d1WdWlV/Mcl3Jnloi/fJ5iwy38ey8qyVVNWeJN+S5NNbuktOJI+vZszjq3nz+Gr38cyGTejuY1X1o1l5F9VTkry3ux+oqh+Zzv+FJB9K8rokh5P8n6z8Sws7wILz/edJ/lKSm6Y6e6y7927XnlncgvNlh1pkvt39UFX9RpJPJPlqkl/u7nU/pouTw4J/ft+Z5JaqOpSVp9z/ZHd/dts2zfNSVe/PyqeInFlVR5K8I8kLE4+v5mCB+Xp8tYMtMF92mVp5liEAAADAGF5GAQAAAAwlNgAAAABDiQ0AAADAUGIDAAAAMJTYAAAAALtIVb23qp6qqg0/kauqvrGqfquq/kdVfaKqXrfIbYgNAAAAsLvckuSKBY/9Z0lu7+7vSLIvyU2LXEhsAAAAgF2kuz+a5HOr16rqm6rqN6rq/qr67ar61mcOT/Li6fRLkjy+yG2cOmy3AAAAwE51IMmPdPenquo7s/IMhu9J8tNJfrOqfizJi5J87yJXJjYAAADALs1ZS28AAADnSURBVFZVZyT5m0n+Q1U9s3za9P1NSW7p7hur6m8k+XdV9aru/up61yk2AAAAwO72giR/0t0XrXHeWzO9v0N3311VX5fkzCRPbXSFAAAAwC7V3V9M8khVvTFJasVrprMfS/Laaf3bknxdkv+90XVWd5+g7QIAAAAnm6p6f5KlrDxD4ckk70jy35LcnOSsJC9McrC7/2VVXZjkl5KckZU3i/yn3f2bG96G2AAAAACM5GUUAAAAwFBiAwAAADCU2AAAAAAMJTYAAAAAQ4kNAAAAwFBiAwAAADCU2AAAAAAMJTYAAAAAQ/0/VzblKVulpDcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_trading_data['mv'].hist(bins=100, figsize=(18, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5777f03f",
   "metadata": {},
   "source": [
    "我们会发现这个分布严重 <font color=\"#FF0000\">右偏</font>，这是因为我国中小市值的公司特别多，市值分布极度不均匀。<br>\n",
    "大的公司如中国平安、工商银行等，市值规模上万亿元；而有的小公司的市值仅有十几亿元甚至数亿元。<br>\n",
    "大市值的公司数量少，中小市值的公司则多如牛毛，这样的市场特征就形成了这样的市值分布。<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f5c3a59",
   "metadata": {},
   "source": [
    "#### 想一想❓\n",
    "\n",
    "小公司和大公司的市值之间虽有上千倍的差距，但是反映在股票市场上，市值因子造成的股票涨跌差距却不会这么大。<br>\n",
    "例如，某一天市场偏好大盘股，那么两只相同行业的股票，其中市值大的股票可能上涨3%，而小盘股可能上涨1.5%，<br>\n",
    "但是这两个公司的市值差异可能是100倍甚至1000倍。<br>\n",
    "这就要求我们对这一因子进行一系列的处理来改变这种因子数据分布的不均衡和不合理。<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0a978b8",
   "metadata": {},
   "source": [
    "#### 如何处理不均衡\n",
    "对市值进行**对数处理**，能够使其分布更接近于正态"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0c2fb17b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_trading_data['size'] = np.log(sub_trading_data['mv'])\n",
    "sub_trading_data['size'].hist(bins=100, figsize=(18, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db160ca3",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c9d36f77",
   "metadata": {},
   "source": [
    "### 如何处理大小盘因子？\n",
    "\n",
    "我们已经定义了大小盘因子，同时采用了对原始因子取对数的方式使得因子的分布更加合理、因子的数值更加贴近金融含义。<br>\n",
    "在这些步骤之后，就需要对因子数据进行处理了。<br>\n",
    "这一部分我们介绍因子处理的3个步骤：**去极值与异常值、标准化、中性化**<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e272fe2",
   "metadata": {},
   "source": [
    "### 去极值与异常值"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d29f940c",
   "metadata": {},
   "source": [
    "#### 去极值  \n",
    "    偏度计算：-0.5~~0.5之间属于正常，0.5-1.0属于有点偏，1以上右偏较严重"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "184b09ff",
   "metadata": {},
   "source": [
    "<font color=\"#800080\">\n",
    "【背景知识】<br>\n",
    "偏度值（Skewness）是描述数据分布对称性的一种统计量，用于衡量数据倾向于偏斜的方向。<br>\n",
    "偏度值的评价大小，通常与数据分布的形状密切相关。<br>\n",
    "偏度值的计算公式为：<br>\n",
    "S = (3 * Σ(xi - μ)² / Σxi) ^ 1/3<br>\n",
    "其中，xi 表示每个数据点，μ 表示均值，Σ表示求和。<br>\n",
    "偏度值的评价标准如下：<br>\n",
    "如果偏度值为 0，表示数据分布是对称的，即正态分布。<br>\n",
    "如果偏度值为正，表示数据分布向右偏斜，即右侧尾部较长。这种情况称为正偏度或右偏度。<br>\n",
    "如果偏度值为负，表示数据分布向左偏斜，即左侧尾部较长。这种情况称为负偏度或左偏度。<br>\n",
    "在实际应用中，我们可以根据偏度值来判断数据分布的形状，并进一步分析数据的特点。<br>\n",
    "一般来说，偏度值越远离 0，数据分布的偏斜程度越大。<br>\n",
    "正负偏度值可以为我们提供关于数据分布对称性的信息，有助于了解数据的内在规律。<br>\n",
    "需要注意的是，偏度值仅是评价数据分布对称性的一种指标，并不能完全反映数据集的质量。<br>\n",
    "在评价数据质量时，还需结合其他统计量（如均值、标准差、变异系数等）以及实际应用场景来进行综合分析。<br>\n",
    "</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2733d36a",
   "metadata": {},
   "source": [
    "<font color=\"#800080\">\n",
    "【背景知识】<br>\n",
    "偏度值的大小并没有一个固定的评价标准，因为它取决于数据的分布形状。<br>\n",
    "然而，在实际应用中，我们可以根据经验来大致判断偏度值是否较大。<br>\n",
    "一般来说，当偏度值绝对值在 1 左右时，可以认为数据分布具有一定的偏斜程度。<br>\n",
    "随着偏度值的增大，数据分布的偏斜程度也会加大。<br>\n",
    "但是，仅凭偏度值来评价数据分布的偏斜程度是有限的，因为偏度值受到数据最大值和最小值的影响。<br>\n",
    "在某些特殊情况下，如样本数据集中在均值附近，而极端值对偏度值产生较大影响时，<br>\n",
    "偏度值可能不能很好地反映数据分布的偏斜程度。<br>\n",
    "在这种情况下，可以考虑使用其他统计量，如熵、四分位差等，来评价数据分布的偏斜程度。<br>\n",
    "总之，在评价偏度值大小时，应结合数据分布的实际情况和应用场景来进行判断。<br>\n",
    "在实际分析过程中，可以参考偏度值的变化趋势，以及与其他统计量的结合分析来得出结论。<br>\n",
    "    </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e381241d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.993571911386947"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_trading_data['mv'].skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "725ae07f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2637189510611557"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_trading_data['size'].skew()\n",
    "# 1.2637189510611557"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57bdc157",
   "metadata": {},
   "source": [
    "<font color=\"#800080\">\n",
    "【背景知识】<br>\n",
    "在这里，skew() 是一个 Pandas 函数，用于计算数据集的歪度。<br>\n",
    "具体来说，它计算的是数据集中每个元素与数据集平均值的差异。<br>\n",
    "sub_trading_data 是一个数据框（DataFrame），其中包含交易数据。size 列表示交易的数量。<br>\n",
    "通过计算 size 列的歪度，你可以了解交易数量分布的不对称性。<br>\n",
    "如果歪度较大，说明交易数量集中在某个区间；<br>\n",
    "如果歪度较小，说明交易数量分布较为平均。<br>\n",
    "需要注意的是，Pandas 中的 skew() 函数默认计算的是基于偏差的歪度（也称为拉普拉斯歪度）。<br>\n",
    "此外，你还可以使用 kurtosis() 函数计算基于峰度的歪度（柯尔指数）。<br>\n",
    "</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0a8f2db",
   "metadata": {},
   "source": [
    "从计算的结果来看，取了对数后的市值分布偏度依然达到约1.26。这样的偏度是由最右侧几个极大的市值造成的。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "387f3d77",
   "metadata": {},
   "source": [
    "在经济学中有一个很简单的原则叫作 **“边际效用递减”**。<br>\n",
    "举个考试的例子，我们稍微一努力就可以把成绩从60分提升到80分；<br>\n",
    "但是从80分提升到90分就需要花费更大的努力；而从90分到100分则更需要加倍的刻苦努力。<br>\n",
    "这就是“努力”这个因子的边际效用递减。同样地，市值因子也是如此。<br>\n",
    "有的股票市值因子的分数是6，有的是2，市值对它们收益率的影响固然会有差异，但是不至于达到3倍之多。<br>\n",
    "为了体现这一点，通常的做法是选择一个 **阈值**，将不在阈值范围之内的因子值进行特殊处理，让其体现出“边际效用递减”这一经济现象。<br>\n",
    "而这些被特殊处理的因子值我们称之为 **“极值”**。 <br>\n",
    "对于极值的处理方法，有一很形象的叫法——**压缩**。<br>\n",
    "当因子值大于或小于某一个阈值的时候，我们就将该因子值设为这一阈值，这一过程体现在分布图上就类似于在两端进行压缩的效果。<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7cd4821",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "29969749",
   "metadata": {},
   "source": [
    "### 3σ   （方法一）\n",
    "\n",
    "我们将**3倍标准差**设为市值因子的阈值，那么就可以使用如下代码对因子值进行压缩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e5b1394d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def filter_extreme_by_sigma(series, n=3):\n",
    "    # 计算均值\n",
    "    mean = series.mean()\n",
    "    # 计算方差\n",
    "    std = series.std()\n",
    "    # 计算上下限的值\n",
    "    max_value = mean + n * std\n",
    "    min_value = mean - n * std\n",
    "    return np.clip(series, min_value, max_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e03e7c84",
   "metadata": {},
   "source": [
    "通过它np.clip(series, min_value, max_value)将极大值和极小值限定为在3倍标准差的范围内\n",
    "\n",
    "np.clip() 是 NumPy 中的一个函数，用于剪辑（clip）输入数组中的元素。<br>\n",
    "这个函数会将输入数组中的每个元素限制在指定的最小值和最大值之间。<br>\n",
    "换句话说，对于数组中的每个元素，<br>\n",
    "如果它小于最小值，那么它将被设置为最小值；<br>\n",
    "如果它大于最大值，那么它将被设置为最大值。<br>\n",
    "\n",
    "这个操作在处理数据时非常有用，可以确保处理的数据始终在一个特定的范围内。<br>\n",
    "例如，在图像处理中，可以使用这个函数来确保图像的像素值始终在一个指定的灰度级别范围内。<br>\n",
    "以下是该函数的语法：<br>\n",
    "复制代码  np.clip(array, min_value, max_value)  <br>\n",
    "参数说明：<br>\n",
    "array：输入的 NumPy 数组。<br>\n",
    "min_value：数组中元素的最小值。<br>\n",
    "max_value：数组中元素的最大值。<br>\n",
    "返回值：剪辑后的数组，其中的每个元素都限制在指定的最小值和最大值之间。<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "61f592d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_trading_data['size_3sigma'] = filter_extreme_by_sigma(sub_trading_data['size'])\n",
    "sub_trading_data['size_3sigma'].skew()\n",
    "sub_trading_data['size_3sigma'].hist(bins=100, figsize=(18, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c0758eb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data_date</th>\n",
       "      <th>secucode</th>\n",
       "      <th>daily_return</th>\n",
       "      <th>mv</th>\n",
       "      <th>free_mv</th>\n",
       "      <th>turnover</th>\n",
       "      <th>ind_code</th>\n",
       "      <th>size</th>\n",
       "      <th>size_3sigma</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>334461</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>0.001619</td>\n",
       "      <td>2.123980e+07</td>\n",
       "      <td>2.123960e+07</td>\n",
       "      <td>0.004936</td>\n",
       "      <td>480000</td>\n",
       "      <td>16.871387</td>\n",
       "      <td>16.371126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334462</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000002.SZ</td>\n",
       "      <td>0.006711</td>\n",
       "      <td>2.625533e+07</td>\n",
       "      <td>2.623096e+07</td>\n",
       "      <td>0.000961</td>\n",
       "      <td>430000</td>\n",
       "      <td>17.083380</td>\n",
       "      <td>16.371126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334463</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000004.SZ</td>\n",
       "      <td>0.087059</td>\n",
       "      <td>1.939861e+05</td>\n",
       "      <td>1.915766e+05</td>\n",
       "      <td>0.007673</td>\n",
       "      <td>370000</td>\n",
       "      <td>12.175542</td>\n",
       "      <td>12.175542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334464</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000005.SZ</td>\n",
       "      <td>0.019802</td>\n",
       "      <td>3.270879e+05</td>\n",
       "      <td>3.269054e+05</td>\n",
       "      <td>0.014683</td>\n",
       "      <td>410000</td>\n",
       "      <td>12.697984</td>\n",
       "      <td>12.697984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334465</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000006.SZ</td>\n",
       "      <td>0.045372</td>\n",
       "      <td>7.775971e+05</td>\n",
       "      <td>7.763248e+05</td>\n",
       "      <td>0.020896</td>\n",
       "      <td>430000</td>\n",
       "      <td>13.563964</td>\n",
       "      <td>13.563964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338036</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603991.SH</td>\n",
       "      <td>0.035249</td>\n",
       "      <td>1.422873e+05</td>\n",
       "      <td>7.841965e+04</td>\n",
       "      <td>0.006144</td>\n",
       "      <td>220000</td>\n",
       "      <td>11.865604</td>\n",
       "      <td>11.865604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338037</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603993.SH</td>\n",
       "      <td>0.015464</td>\n",
       "      <td>6.960314e+06</td>\n",
       "      <td>6.960314e+06</td>\n",
       "      <td>0.007321</td>\n",
       "      <td>240000</td>\n",
       "      <td>15.755735</td>\n",
       "      <td>15.755735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338038</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603997.SH</td>\n",
       "      <td>0.030383</td>\n",
       "      <td>4.987423e+05</td>\n",
       "      <td>4.928593e+05</td>\n",
       "      <td>0.007838</td>\n",
       "      <td>280000</td>\n",
       "      <td>13.119845</td>\n",
       "      <td>13.119845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338039</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603998.SH</td>\n",
       "      <td>0.037820</td>\n",
       "      <td>4.073690e+05</td>\n",
       "      <td>3.967085e+05</td>\n",
       "      <td>0.064843</td>\n",
       "      <td>370000</td>\n",
       "      <td>12.917475</td>\n",
       "      <td>12.917475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338040</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603999.SH</td>\n",
       "      <td>0.033028</td>\n",
       "      <td>3.242880e+05</td>\n",
       "      <td>3.242880e+05</td>\n",
       "      <td>0.012597</td>\n",
       "      <td>720000</td>\n",
       "      <td>12.689387</td>\n",
       "      <td>12.689387</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3580 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         data_date   secucode  daily_return            mv       free_mv  \\\n",
       "334461  2019-05-27  000001.SZ      0.001619  2.123980e+07  2.123960e+07   \n",
       "334462  2019-05-27  000002.SZ      0.006711  2.625533e+07  2.623096e+07   \n",
       "334463  2019-05-27  000004.SZ      0.087059  1.939861e+05  1.915766e+05   \n",
       "334464  2019-05-27  000005.SZ      0.019802  3.270879e+05  3.269054e+05   \n",
       "334465  2019-05-27  000006.SZ      0.045372  7.775971e+05  7.763248e+05   \n",
       "...            ...        ...           ...           ...           ...   \n",
       "338036  2019-05-27  603991.SH      0.035249  1.422873e+05  7.841965e+04   \n",
       "338037  2019-05-27  603993.SH      0.015464  6.960314e+06  6.960314e+06   \n",
       "338038  2019-05-27  603997.SH      0.030383  4.987423e+05  4.928593e+05   \n",
       "338039  2019-05-27  603998.SH      0.037820  4.073690e+05  3.967085e+05   \n",
       "338040  2019-05-27  603999.SH      0.033028  3.242880e+05  3.242880e+05   \n",
       "\n",
       "        turnover  ind_code       size  size_3sigma  \n",
       "334461  0.004936    480000  16.871387    16.371126  \n",
       "334462  0.000961    430000  17.083380    16.371126  \n",
       "334463  0.007673    370000  12.175542    12.175542  \n",
       "334464  0.014683    410000  12.697984    12.697984  \n",
       "334465  0.020896    430000  13.563964    13.563964  \n",
       "...          ...       ...        ...          ...  \n",
       "338036  0.006144    220000  11.865604    11.865604  \n",
       "338037  0.007321    240000  15.755735    15.755735  \n",
       "338038  0.007838    280000  13.119845    13.119845  \n",
       "338039  0.064843    370000  12.917475    12.917475  \n",
       "338040  0.012597    720000  12.689387    12.689387  \n",
       "\n",
       "[3580 rows x 9 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_trading_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "59ac320e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.985818288329592"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 限定3倍标准差后，再做偏度计算，就从1.2637189510611557降为0.985818288329592\n",
    "sub_trading_data['size_3sigma'].skew()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71a10b07",
   "metadata": {},
   "source": [
    "### MAD（Median Absolute Deviation 绝对中位数法）   （方法二）更合理更常见"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c7d8bb5",
   "metadata": {},
   "source": [
    "**MAD（Median Absolute Deviation 绝对中位数法）**\n",
    "\n",
    "$$\n",
    "M A D=\\operatorname{median}\\left(\\left|f_{i}-\\operatorname{Median}_{f}\\right|\\right)\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b594c649",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MAD\n",
    "def filter_extreme_by_MAD(series, n=3):\n",
    "    # 计算中位数 𝑥_𝑚𝑒𝑑𝑖𝑎𝑛\n",
    "    median = series.median()\n",
    "    # 计算绝对偏差值的中位数 MAD\n",
    "    median_new = abs(series - median).median()\n",
    "    # 计算上下限的值\n",
    "    max_value = median + n * median_new\n",
    "    min_value = median - n * median_new\n",
    "    return np.clip(series, min_value, max_value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "97f13c3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4543360104714586"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用绝对中位数法，偏度下降更大（接近正态分布，但是极值比较多）\n",
    "sub_trading_data['size_mad'] = filter_extreme_by_MAD(sub_trading_data['size'])\n",
    "sub_trading_data['size_mad'].skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0d077549",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_trading_data['size_mad'].hist(bins=100, figsize=(18, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5965f67",
   "metadata": {},
   "source": [
    "### 百分位法    （方法三）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "45bb4860",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 百分位法\n",
    "def filter_extreme_by_percentile(series, low=0.025, high=0.975):\n",
    "    # 将数据进行排序\n",
    "    series = series.sort_values()\n",
    "    # 计算上下百分比的分位数\n",
    "    quantiles = series.quantile([low, high])\n",
    "    return np.clip(series, quantiles.iloc[0], quantiles.iloc[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "75cac425",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8871204474154001"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 百分位法 偏度下降有限\n",
    "sub_trading_data['size_percentile'] = filter_extreme_by_percentile(sub_trading_data['size'])\n",
    "sub_trading_data['size_percentile'].skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5fb4328a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_trading_data['size_percentile'].hist(bins=100, figsize=(18, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecae1ff8",
   "metadata": {},
   "source": [
    "### 异常值\n",
    "\n",
    "数据源或者某些突发情况造成数据失真，或是我们知道某些公司的财务数据确实存在问题，这些存在问题的数据称为异常值。<br>\n",
    "在计算市值因子的时候我们很少碰到这样的问题，而当计算一些财务因子时，往往会碰到异常值。<br>\n",
    "\n",
    "假设两家上市公司的总市值都是100亿元，其中一家当年利润是-10亿元，另一家是10亿元。<br>\n",
    "我们按照PE的计算公式分别计算各自的PE，会发现它们的PE分别是-10和10。<br>\n",
    "按照估值因子的逻辑，我们会选择PE比较小的股票，因为其估值较低。<br>\n",
    "但是根据前面的情景，PE为-10的这家上市公司实际情况是亏损的，并不一定具有很好的投资价值。<br>\n",
    "也就是说，当PE小于0的时候，其实这一指标已经变得没有意义了，这时应该进行相应的处理。<br>\n",
    "\n",
    "PE → EP"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e79c98c3",
   "metadata": {},
   "source": [
    "### 标准化"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4500f0c3",
   "metadata": {},
   "source": [
    "#### 为什么要标准化？\n",
    "标准化的作用就是**去除因子的量纲**，让每一个因子之间都可以进行比较、相互叠加。<br>\n",
    "根据之前介绍的多因子模型框架图，最后这些单因子是需要进行组合的，而**因子合成的前提就是这些因子具有相同的量纲**。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a63a280",
   "metadata": {},
   "source": [
    "<font color=\"#800080\">\n",
    "【背景知识】<br>\n",
    "Z-score（Z 分数），又称标准分数，是一种描述一个数据点在一个数据集中相对于均值和标准差的位置的度量。<br>\n",
    "它是由美国统计学家威廉·戈塞（William Gosset）在 20 世纪初提出的，主要用于描述正态分布曲线上的数据点。<br>\n",
    "    \n",
    "Z-score 的计算公式是：<br>\n",
    "Z = (X - μ) / σ<br>\n",
    "其中，Z 是 Z-score，X 是数据点的数值，μ是数据集的均值，σ是数据集的标准差。<br>\n",
    "    \n",
    "Z-score 具有以下特点：<br>\n",
    "1. 如果 Z-score 为 0，表示该数据点等于均值；  <br>\n",
    "2. 如果 Z-score 为正，表示该数据点高于均值；  <br>\n",
    "3. 如果 Z-score 为负，表示该数据点低于均值。<br>\n",
    "    \n",
    "Z-score 可以用于评估数据点在整个数据集中的相对位置，以及数据点之间的差异。<br>\n",
    "当对多个数据集进行比较时，Z-score 可以帮助我们了解各个数据集的分布情况，并消除原始数据量纲的影响。<br>\n",
    "此外，在实际应用中，Z-score 还被用于成绩排名、经济学指标、生物学研究等领域。<br>\n",
    "</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "de83d44c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# z-score\n",
    "def standard_normalize(series):\n",
    "    # 计算均值和方差，z_score标准化\n",
    "    mean = series.mean()\n",
    "    std = series.std()\n",
    "    return (series - mean) / std\n",
    "\n",
    "\n",
    "# max-min\n",
    "def max_min_normalize(series):\n",
    "    # 计算最大值和最小值\n",
    "    max_value = series.max()\n",
    "    min_value = series.min()\n",
    "    # 无量纲标准化序列\n",
    "    return (series - min_value) / (max_value - min_value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bf012bd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1296x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3sigma做了标准化standard_normalize后，图形基本没有变化，但是横坐标发生了变化，原先主要集中在12-14，现在基本以0轴为中心的对称分布\n",
    "sub_trading_data['size_3sigma_std'] = standard_normalize(sub_trading_data['size_3sigma'])\n",
    "sub_trading_data['size_3sigma_std'].hist(bins=100, figsize=(18, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "945f6813",
   "metadata": {},
   "source": [
    "对比被标准化前后两张市值因子的分布图，<br>\n",
    "我们发现，两张因子分布图的**形状没有任何变化**，但是**横轴的数值范围和大小发生了较大的改变**。<br>\n",
    "被标准化之后的因子值分布围绕着0，而且正负数值都有。<br>\n",
    "也就是说，这个时候的因子值已经不再是“市值”的概念了，而是与同一天股票的市值进行比较之后进行了打分，<br>\n",
    "是一个“分值”的概念，这也是为什么被标准化后的因子值称为“Z-score”的原因<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5480ffa",
   "metadata": {},
   "source": [
    "### 中性化"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4ea5d3e",
   "metadata": {},
   "source": [
    "**将上面处理好的因子，作为最终衡量“市值大小”这一股价影响因素是否合理？**<br>\n",
    "\n",
    "在讨论是否合理之前，我们先来讨论一下拳击这项运动。<br>\n",
    "运动爱好者在看拳击比赛的时候经常会听到一个词：量级，而且在比赛过程中会根据参赛选手的量级进行分组。<br>\n",
    "标准的职业拳击比赛可以分成17个级别，最轻的是48公斤级；最重的是86公斤级以上。<br>\n",
    "那么为什么拳击比赛要分重量级别？这个问题很简单，就是体重是决定拳击运动输赢的一个重要因素。<br>\n",
    "48公斤级的选手即使技术再好，反应再快，在86公斤级的选手面前，也往往显得不堪一击。<br>\n",
    "同样，因子也存在这种情况。<br>\n",
    "以市值因子为例，有的行业的公司市值就是大，比如银行；<br>\n",
    "有些行业是典型的轻资产成长型行业，例如传媒。<br>\n",
    "上面计算因子的过程其实如同把所有的行业放在一个擂台上进行拳击比赛，这显然是不合理的。<br>\n",
    "我们就要通过数据处理的方法来解决这个不合理的问题。这一方法就是中性化。<br>\n",
    "从之前的讨论中我们发现，对于市值因子，最不合理的做法就是不对行业进行区分。<br>\n",
    "在实际操作过程中，对行业进行区分的进一步处理的方法叫作**“行业中性化”**。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56ae61b1",
   "metadata": {},
   "source": [
    "**行业中性化有两种方法<br>\n",
    "方法一：回归法<br>\n",
    "方法二：均值法<br>**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bae4753",
   "metadata": {},
   "source": [
    "#### 回归取残差法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b492be93",
   "metadata": {},
   "outputs": [],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "def industry_neutralization(factor_df, factor_name):\n",
    "    # 将行业变成哑变量后再作为解释变量，而需要中性化的因子则作为被解释变量进行回归。回归的残差项就是被中性化后的因子值\n",
    "    # 如果用行业哑变量来解释因子值，那么不能被行业解释的那一部分就是剔除了行业因素后的因子值。\n",
    "    # 而剔除了行业因素的因子值就是回归模型的残差项，这也正是我们希望获得的行业中性化之后的结果\n",
    "    result = sm.OLS(factor_df[factor_name], factor_df[list(factor_df.ind_code.unique())]).fit()\n",
    "    result.summary()\n",
    "    return result.resid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "84775586",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_trading_data = pd.concat([sub_trading_data, pd.get_dummies(sub_trading_data['ind_code'])], axis=1)\n",
    "sub_trading_data['size_factor_neuted'] = industry_neutralization(sub_trading_data, 'size_3sigma_std')\n",
    "sub_trading_data[['data_date', 'secucode', 'ind_code', 'size_3sigma_std', 'size_factor_neuted']]\n",
    "\n",
    "sub_trading_data[['size_3sigma_std', 'size_factor_neuted']].hist(bins=100,figsize=(18, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1d335a5",
   "metadata": {},
   "source": [
    "1、左图是被中性化前的因子值分布直方图；右图是被中性化之后的因子值分布直方图。<br>\n",
    "   可以发现，单纯从分布形状来看，做了行业中性化之后的因子值分布图更加匀称，但不存在质的变化<br>\n",
    "2、有些因子值在被中性化之后会超过之前设定的-3、+3的阈值。<br>\n",
    "   如果有必要，我们可在中性化之后对部分因子再进行一次去极值的处理<br>"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "8426d5ac",
   "metadata": {},
   "source": [
    " <font color=\"#FF0000\">**tips：回归结果怎么看？**</font> ——视频第17分钟\n",
    " \n",
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f0ca9ec5",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>     <td>size_3sigma_std</td> <th>  R-squared:         </th> <td>   0.159</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.153</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   24.87</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Wed, 18 Oct 2023</td> <th>  Prob (F-statistic):</th> <td>7.40e-113</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>23:14:06</td>     <th>  Log-Likelihood:    </th> <td> -4769.3</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>  3580</td>      <th>  AIC:               </th> <td>   9595.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>  3552</td>      <th>  BIC:               </th> <td>   9768.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>    27</td>      <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "     <td></td>       <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>480000</th> <td>    1.1347</td> <td>    0.081</td> <td>   13.946</td> <td> 0.000</td> <td>    0.975</td> <td>    1.294</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>480000</th> <td>    1.1347</td> <td>    0.081</td> <td>   13.946</td> <td> 0.000</td> <td>    0.975</td> <td>    1.294</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>430000</th> <td>    0.1088</td> <td>    0.038</td> <td>    2.836</td> <td> 0.005</td> <td>    0.034</td> <td>    0.184</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>430000</th> <td>    0.1088</td> <td>    0.038</td> <td>    2.836</td> <td> 0.005</td> <td>    0.034</td> <td>    0.184</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>370000</th> <td>    0.0761</td> <td>    0.028</td> <td>    2.766</td> <td> 0.006</td> <td>    0.022</td> <td>    0.130</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>370000</th> <td>    0.0761</td> <td>    0.028</td> <td>    2.766</td> <td> 0.006</td> <td>    0.022</td> <td>    0.130</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>410000</th> <td>    0.0315</td> <td>    0.037</td> <td>    0.859</td> <td> 0.390</td> <td>   -0.040</td> <td>    0.103</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>410000</th> <td>    0.0315</td> <td>    0.037</td> <td>    0.859</td> <td> 0.390</td> <td>   -0.040</td> <td>    0.103</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>640000</th> <td>   -0.2285</td> <td>    0.025</td> <td>   -9.209</td> <td> 0.000</td> <td>   -0.277</td> <td>   -0.180</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>640000</th> <td>   -0.2285</td> <td>    0.025</td> <td>   -9.209</td> <td> 0.000</td> <td>   -0.277</td> <td>   -0.180</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>510000</th> <td>   -0.1659</td> <td>    0.067</td> <td>   -2.471</td> <td> 0.014</td> <td>   -0.298</td> <td>   -0.034</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>510000</th> <td>   -0.1659</td> <td>    0.067</td> <td>   -2.471</td> <td> 0.014</td> <td>   -0.298</td> <td>   -0.034</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>620000</th> <td>   -0.0263</td> <td>    0.041</td> <td>   -0.639</td> <td> 0.523</td> <td>   -0.107</td> <td>    0.054</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>620000</th> <td>   -0.0263</td> <td>    0.041</td> <td>   -0.639</td> <td> 0.523</td> <td>   -0.107</td> <td>    0.054</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>610000</th> <td>   -0.1153</td> <td>    0.049</td> <td>   -2.337</td> <td> 0.020</td> <td>   -0.212</td> <td>   -0.019</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>610000</th> <td>   -0.1153</td> <td>    0.049</td> <td>   -2.337</td> <td> 0.020</td> <td>   -0.212</td> <td>   -0.019</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>330000</th> <td>   -0.0736</td> <td>    0.055</td> <td>   -1.337</td> <td> 0.181</td> <td>   -0.181</td> <td>    0.034</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>330000</th> <td>   -0.0736</td> <td>    0.055</td> <td>   -1.337</td> <td> 0.181</td> <td>   -0.181</td> <td>    0.034</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>340000</th> <td>    0.1569</td> <td>    0.046</td> <td>    3.442</td> <td> 0.001</td> <td>    0.068</td> <td>    0.246</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>340000</th> <td>    0.1569</td> <td>    0.046</td> <td>    3.442</td> <td> 0.001</td> <td>    0.068</td> <td>    0.246</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>270000</th> <td>    0.0258</td> <td>    0.031</td> <td>    0.833</td> <td> 0.405</td> <td>   -0.035</td> <td>    0.087</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>270000</th> <td>    0.0258</td> <td>    0.031</td> <td>    0.833</td> <td> 0.405</td> <td>   -0.035</td> <td>    0.087</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>280000</th> <td>   -0.1010</td> <td>    0.034</td> <td>   -2.951</td> <td> 0.003</td> <td>   -0.168</td> <td>   -0.034</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>280000</th> <td>   -0.1010</td> <td>    0.034</td> <td>   -2.951</td> <td> 0.003</td> <td>   -0.168</td> <td>   -0.034</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>450000</th> <td>   -0.0748</td> <td>    0.047</td> <td>   -1.593</td> <td> 0.111</td> <td>   -0.167</td> <td>    0.017</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>450000</th> <td>   -0.0748</td> <td>    0.047</td> <td>   -1.593</td> <td> 0.111</td> <td>   -0.167</td> <td>    0.017</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>730000</th> <td>   -0.0219</td> <td>    0.041</td> <td>   -0.531</td> <td> 0.596</td> <td>   -0.103</td> <td>    0.059</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>730000</th> <td>   -0.0219</td> <td>    0.041</td> <td>   -0.531</td> <td> 0.596</td> <td>   -0.103</td> <td>    0.059</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>720000</th> <td>    0.0153</td> <td>    0.039</td> <td>    0.393</td> <td> 0.695</td> <td>   -0.061</td> <td>    0.092</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>720000</th> <td>    0.0153</td> <td>    0.039</td> <td>    0.393</td> <td> 0.695</td> <td>   -0.061</td> <td>    0.092</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>110000</th> <td>   -0.0216</td> <td>    0.049</td> <td>   -0.439</td> <td> 0.661</td> <td>   -0.118</td> <td>    0.075</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>110000</th> <td>   -0.0216</td> <td>    0.049</td> <td>   -0.439</td> <td> 0.661</td> <td>   -0.118</td> <td>    0.075</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>220000</th> <td>   -0.1075</td> <td>    0.025</td> <td>   -4.308</td> <td> 0.000</td> <td>   -0.156</td> <td>   -0.059</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>220000</th> <td>   -0.1075</td> <td>    0.025</td> <td>   -4.308</td> <td> 0.000</td> <td>   -0.156</td> <td>   -0.059</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>240000</th> <td>    0.0755</td> <td>    0.045</td> <td>    1.688</td> <td> 0.092</td> <td>   -0.012</td> <td>    0.163</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>240000</th> <td>    0.0755</td> <td>    0.045</td> <td>    1.688</td> <td> 0.092</td> <td>   -0.012</td> <td>    0.163</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>710000</th> <td>    0.0131</td> <td>    0.033</td> <td>    0.399</td> <td> 0.690</td> <td>   -0.051</td> <td>    0.078</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>710000</th> <td>    0.0131</td> <td>    0.033</td> <td>    0.399</td> <td> 0.690</td> <td>   -0.051</td> <td>    0.078</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>420000</th> <td>    0.2237</td> <td>    0.044</td> <td>    5.099</td> <td> 0.000</td> <td>    0.138</td> <td>    0.310</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>420000</th> <td>    0.2237</td> <td>    0.044</td> <td>    5.099</td> <td> 0.000</td> <td>    0.138</td> <td>    0.310</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>490000</th> <td>    0.8146</td> <td>    0.056</td> <td>   14.487</td> <td> 0.000</td> <td>    0.704</td> <td>    0.925</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>490000</th> <td>    0.8146</td> <td>    0.056</td> <td>   14.487</td> <td> 0.000</td> <td>    0.704</td> <td>    0.925</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>630000</th> <td>   -0.0943</td> <td>    0.037</td> <td>   -2.574</td> <td> 0.010</td> <td>   -0.166</td> <td>   -0.022</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>630000</th> <td>   -0.0943</td> <td>    0.037</td> <td>   -2.574</td> <td> 0.010</td> <td>   -0.166</td> <td>   -0.022</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>460000</th> <td>   -0.1576</td> <td>    0.083</td> <td>   -1.906</td> <td> 0.057</td> <td>   -0.320</td> <td>    0.004</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>460000</th> <td>   -0.1576</td> <td>    0.083</td> <td>   -1.906</td> <td> 0.057</td> <td>   -0.320</td> <td>    0.004</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>360000</th> <td>   -0.1505</td> <td>    0.045</td> <td>   -3.350</td> <td> 0.001</td> <td>   -0.239</td> <td>   -0.062</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>360000</th> <td>   -0.1505</td> <td>    0.045</td> <td>   -3.350</td> <td> 0.001</td> <td>   -0.239</td> <td>   -0.062</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>650000</th> <td>    0.2247</td> <td>    0.059</td> <td>    3.813</td> <td> 0.000</td> <td>    0.109</td> <td>    0.340</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>650000</th> <td>    0.2247</td> <td>    0.059</td> <td>    3.813</td> <td> 0.000</td> <td>    0.109</td> <td>    0.340</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>210000</th> <td>    0.2651</td> <td>    0.077</td> <td>    3.456</td> <td> 0.001</td> <td>    0.115</td> <td>    0.415</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>210000</th> <td>    0.2651</td> <td>    0.077</td> <td>    3.456</td> <td> 0.001</td> <td>    0.115</td> <td>    0.415</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>350000</th> <td>   -0.2166</td> <td>    0.049</td> <td>   -4.414</td> <td> 0.000</td> <td>   -0.313</td> <td>   -0.120</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>350000</th> <td>   -0.2166</td> <td>    0.049</td> <td>   -4.414</td> <td> 0.000</td> <td>   -0.313</td> <td>   -0.120</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>230000</th> <td>    0.2454</td> <td>    0.069</td> <td>    3.576</td> <td> 0.000</td> <td>    0.111</td> <td>    0.380</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>230000</th> <td>    0.2454</td> <td>    0.069</td> <td>    3.576</td> <td> 0.000</td> <td>    0.111</td> <td>    0.380</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>405.915</td> <th>  Durbin-Watson:     </th> <td>   1.722</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td> 577.756</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 0.867</td>  <th>  Prob(JB):          </th> <td>3.48e-126</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 3.930</td>  <th>  Cond. No.          </th> <td>2.13e+16</td> \n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The smallest eigenvalue is 1.51e-30. This might indicate that there are<br/>strong multicollinearity problems or that the design matrix is singular."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:        size_3sigma_std   R-squared:                       0.159\n",
       "Model:                            OLS   Adj. R-squared:                  0.153\n",
       "Method:                 Least Squares   F-statistic:                     24.87\n",
       "Date:                Wed, 18 Oct 2023   Prob (F-statistic):          7.40e-113\n",
       "Time:                        23:14:06   Log-Likelihood:                -4769.3\n",
       "No. Observations:                3580   AIC:                             9595.\n",
       "Df Residuals:                    3552   BIC:                             9768.\n",
       "Df Model:                          27                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "480000         1.1347      0.081     13.946      0.000       0.975       1.294\n",
       "480000         1.1347      0.081     13.946      0.000       0.975       1.294\n",
       "430000         0.1088      0.038      2.836      0.005       0.034       0.184\n",
       "430000         0.1088      0.038      2.836      0.005       0.034       0.184\n",
       "370000         0.0761      0.028      2.766      0.006       0.022       0.130\n",
       "370000         0.0761      0.028      2.766      0.006       0.022       0.130\n",
       "410000         0.0315      0.037      0.859      0.390      -0.040       0.103\n",
       "410000         0.0315      0.037      0.859      0.390      -0.040       0.103\n",
       "640000        -0.2285      0.025     -9.209      0.000      -0.277      -0.180\n",
       "640000        -0.2285      0.025     -9.209      0.000      -0.277      -0.180\n",
       "510000        -0.1659      0.067     -2.471      0.014      -0.298      -0.034\n",
       "510000        -0.1659      0.067     -2.471      0.014      -0.298      -0.034\n",
       "620000        -0.0263      0.041     -0.639      0.523      -0.107       0.054\n",
       "620000        -0.0263      0.041     -0.639      0.523      -0.107       0.054\n",
       "610000        -0.1153      0.049     -2.337      0.020      -0.212      -0.019\n",
       "610000        -0.1153      0.049     -2.337      0.020      -0.212      -0.019\n",
       "330000        -0.0736      0.055     -1.337      0.181      -0.181       0.034\n",
       "330000        -0.0736      0.055     -1.337      0.181      -0.181       0.034\n",
       "340000         0.1569      0.046      3.442      0.001       0.068       0.246\n",
       "340000         0.1569      0.046      3.442      0.001       0.068       0.246\n",
       "270000         0.0258      0.031      0.833      0.405      -0.035       0.087\n",
       "270000         0.0258      0.031      0.833      0.405      -0.035       0.087\n",
       "280000        -0.1010      0.034     -2.951      0.003      -0.168      -0.034\n",
       "280000        -0.1010      0.034     -2.951      0.003      -0.168      -0.034\n",
       "450000        -0.0748      0.047     -1.593      0.111      -0.167       0.017\n",
       "450000        -0.0748      0.047     -1.593      0.111      -0.167       0.017\n",
       "730000        -0.0219      0.041     -0.531      0.596      -0.103       0.059\n",
       "730000        -0.0219      0.041     -0.531      0.596      -0.103       0.059\n",
       "720000         0.0153      0.039      0.393      0.695      -0.061       0.092\n",
       "720000         0.0153      0.039      0.393      0.695      -0.061       0.092\n",
       "110000        -0.0216      0.049     -0.439      0.661      -0.118       0.075\n",
       "110000        -0.0216      0.049     -0.439      0.661      -0.118       0.075\n",
       "220000        -0.1075      0.025     -4.308      0.000      -0.156      -0.059\n",
       "220000        -0.1075      0.025     -4.308      0.000      -0.156      -0.059\n",
       "240000         0.0755      0.045      1.688      0.092      -0.012       0.163\n",
       "240000         0.0755      0.045      1.688      0.092      -0.012       0.163\n",
       "710000         0.0131      0.033      0.399      0.690      -0.051       0.078\n",
       "710000         0.0131      0.033      0.399      0.690      -0.051       0.078\n",
       "420000         0.2237      0.044      5.099      0.000       0.138       0.310\n",
       "420000         0.2237      0.044      5.099      0.000       0.138       0.310\n",
       "490000         0.8146      0.056     14.487      0.000       0.704       0.925\n",
       "490000         0.8146      0.056     14.487      0.000       0.704       0.925\n",
       "630000        -0.0943      0.037     -2.574      0.010      -0.166      -0.022\n",
       "630000        -0.0943      0.037     -2.574      0.010      -0.166      -0.022\n",
       "460000        -0.1576      0.083     -1.906      0.057      -0.320       0.004\n",
       "460000        -0.1576      0.083     -1.906      0.057      -0.320       0.004\n",
       "360000        -0.1505      0.045     -3.350      0.001      -0.239      -0.062\n",
       "360000        -0.1505      0.045     -3.350      0.001      -0.239      -0.062\n",
       "650000         0.2247      0.059      3.813      0.000       0.109       0.340\n",
       "650000         0.2247      0.059      3.813      0.000       0.109       0.340\n",
       "210000         0.2651      0.077      3.456      0.001       0.115       0.415\n",
       "210000         0.2651      0.077      3.456      0.001       0.115       0.415\n",
       "350000        -0.2166      0.049     -4.414      0.000      -0.313      -0.120\n",
       "350000        -0.2166      0.049     -4.414      0.000      -0.313      -0.120\n",
       "230000         0.2454      0.069      3.576      0.000       0.111       0.380\n",
       "230000         0.2454      0.069      3.576      0.000       0.111       0.380\n",
       "==============================================================================\n",
       "Omnibus:                      405.915   Durbin-Watson:                   1.722\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              577.756\n",
       "Skew:                           0.867   Prob(JB):                    3.48e-126\n",
       "Kurtosis:                       3.930   Cond. No.                     2.13e+16\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The smallest eigenvalue is 1.51e-30. This might indicate that there are\n",
       "strong multicollinearity problems or that the design matrix is singular.\n",
       "\"\"\""
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = sm.OLS(sub_trading_data['size_3sigma_std'], sub_trading_data[list(sub_trading_data.ind_code.unique())]).fit()\n",
    "result.summary()"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "6506d958",
   "metadata": {},
   "source": [
    "![image-2.png](attachment:image-2.png)\n",
    " 1、左图是被中性化前的因子值分布直方图；右图是被中性化之后的因子值分布直方图。<br>\n",
    "   可以发现，单纯从分布形状来看，做了行业中性化之后的因子值分布图更加匀称，但不存在质的变化<br>\n",
    "2、有些因子值在被中性化之后会超过之前设定的-3、+3的阈值。<br>\n",
    "   如果有必要，我们可在中性化之后对部分因子再进行一次去极值的处理<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "fba6507d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data_date</th>\n",
       "      <th>secucode</th>\n",
       "      <th>daily_return</th>\n",
       "      <th>mv</th>\n",
       "      <th>free_mv</th>\n",
       "      <th>turnover</th>\n",
       "      <th>ind_code</th>\n",
       "      <th>size</th>\n",
       "      <th>size_3sigma</th>\n",
       "      <th>size_mad</th>\n",
       "      <th>...</th>\n",
       "      <th>510000</th>\n",
       "      <th>610000</th>\n",
       "      <th>620000</th>\n",
       "      <th>630000</th>\n",
       "      <th>640000</th>\n",
       "      <th>650000</th>\n",
       "      <th>710000</th>\n",
       "      <th>720000</th>\n",
       "      <th>730000</th>\n",
       "      <th>size_factor_neuted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>334461</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>0.001619</td>\n",
       "      <td>2.123980e+07</td>\n",
       "      <td>2.123960e+07</td>\n",
       "      <td>0.004936</td>\n",
       "      <td>480000</td>\n",
       "      <td>16.871387</td>\n",
       "      <td>16.371126</td>\n",
       "      <td>14.869342</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.859205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334462</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000002.SZ</td>\n",
       "      <td>0.006711</td>\n",
       "      <td>2.625533e+07</td>\n",
       "      <td>2.623096e+07</td>\n",
       "      <td>0.000961</td>\n",
       "      <td>430000</td>\n",
       "      <td>17.083380</td>\n",
       "      <td>16.371126</td>\n",
       "      <td>14.869342</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.911020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334463</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000004.SZ</td>\n",
       "      <td>0.087059</td>\n",
       "      <td>1.939861e+05</td>\n",
       "      <td>1.915766e+05</td>\n",
       "      <td>0.007673</td>\n",
       "      <td>370000</td>\n",
       "      <td>12.175542</td>\n",
       "      <td>12.175542</td>\n",
       "      <td>12.175542</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.323925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334464</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000005.SZ</td>\n",
       "      <td>0.019802</td>\n",
       "      <td>3.270879e+05</td>\n",
       "      <td>3.269054e+05</td>\n",
       "      <td>0.014683</td>\n",
       "      <td>410000</td>\n",
       "      <td>12.697984</td>\n",
       "      <td>12.697984</td>\n",
       "      <td>12.697984</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.699192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334465</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>000006.SZ</td>\n",
       "      <td>0.045372</td>\n",
       "      <td>7.775971e+05</td>\n",
       "      <td>7.763248e+05</td>\n",
       "      <td>0.020896</td>\n",
       "      <td>430000</td>\n",
       "      <td>13.563964</td>\n",
       "      <td>13.563964</td>\n",
       "      <td>13.563964</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.033776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338036</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603991.SH</td>\n",
       "      <td>0.035249</td>\n",
       "      <td>1.422873e+05</td>\n",
       "      <td>7.841965e+04</td>\n",
       "      <td>0.006144</td>\n",
       "      <td>220000</td>\n",
       "      <td>11.865604</td>\n",
       "      <td>11.865604</td>\n",
       "      <td>11.865604</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.274328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338037</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603993.SH</td>\n",
       "      <td>0.015464</td>\n",
       "      <td>6.960314e+06</td>\n",
       "      <td>6.960314e+06</td>\n",
       "      <td>0.007321</td>\n",
       "      <td>240000</td>\n",
       "      <td>15.755735</td>\n",
       "      <td>15.755735</td>\n",
       "      <td>14.869342</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.346924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338038</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603997.SH</td>\n",
       "      <td>0.030383</td>\n",
       "      <td>4.987423e+05</td>\n",
       "      <td>4.928593e+05</td>\n",
       "      <td>0.007838</td>\n",
       "      <td>280000</td>\n",
       "      <td>13.119845</td>\n",
       "      <td>13.119845</td>\n",
       "      <td>13.119845</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.001917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338039</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603998.SH</td>\n",
       "      <td>0.037820</td>\n",
       "      <td>4.073690e+05</td>\n",
       "      <td>3.967085e+05</td>\n",
       "      <td>0.064843</td>\n",
       "      <td>370000</td>\n",
       "      <td>12.917475</td>\n",
       "      <td>12.917475</td>\n",
       "      <td>12.917475</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.563470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338040</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>603999.SH</td>\n",
       "      <td>0.033028</td>\n",
       "      <td>3.242880e+05</td>\n",
       "      <td>3.242880e+05</td>\n",
       "      <td>0.012597</td>\n",
       "      <td>720000</td>\n",
       "      <td>12.689387</td>\n",
       "      <td>12.689387</td>\n",
       "      <td>12.689387</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.675732</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3580 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         data_date   secucode  daily_return            mv       free_mv  \\\n",
       "334461  2019-05-27  000001.SZ      0.001619  2.123980e+07  2.123960e+07   \n",
       "334462  2019-05-27  000002.SZ      0.006711  2.625533e+07  2.623096e+07   \n",
       "334463  2019-05-27  000004.SZ      0.087059  1.939861e+05  1.915766e+05   \n",
       "334464  2019-05-27  000005.SZ      0.019802  3.270879e+05  3.269054e+05   \n",
       "334465  2019-05-27  000006.SZ      0.045372  7.775971e+05  7.763248e+05   \n",
       "...            ...        ...           ...           ...           ...   \n",
       "338036  2019-05-27  603991.SH      0.035249  1.422873e+05  7.841965e+04   \n",
       "338037  2019-05-27  603993.SH      0.015464  6.960314e+06  6.960314e+06   \n",
       "338038  2019-05-27  603997.SH      0.030383  4.987423e+05  4.928593e+05   \n",
       "338039  2019-05-27  603998.SH      0.037820  4.073690e+05  3.967085e+05   \n",
       "338040  2019-05-27  603999.SH      0.033028  3.242880e+05  3.242880e+05   \n",
       "\n",
       "        turnover  ind_code       size  size_3sigma   size_mad  ...  510000  \\\n",
       "334461  0.004936    480000  16.871387    16.371126  14.869342  ...       0   \n",
       "334462  0.000961    430000  17.083380    16.371126  14.869342  ...       0   \n",
       "334463  0.007673    370000  12.175542    12.175542  12.175542  ...       0   \n",
       "334464  0.014683    410000  12.697984    12.697984  12.697984  ...       0   \n",
       "334465  0.020896    430000  13.563964    13.563964  13.563964  ...       0   \n",
       "...          ...       ...        ...          ...        ...  ...     ...   \n",
       "338036  0.006144    220000  11.865604    11.865604  11.865604  ...       0   \n",
       "338037  0.007321    240000  15.755735    15.755735  14.869342  ...       0   \n",
       "338038  0.007838    280000  13.119845    13.119845  13.119845  ...       0   \n",
       "338039  0.064843    370000  12.917475    12.917475  12.917475  ...       0   \n",
       "338040  0.012597    720000  12.689387    12.689387  12.689387  ...       0   \n",
       "\n",
       "        610000  620000  630000  640000  650000  710000  720000  730000  \\\n",
       "334461       0       0       0       0       0       0       0       0   \n",
       "334462       0       0       0       0       0       0       0       0   \n",
       "334463       0       0       0       0       0       0       0       0   \n",
       "334464       0       0       0       0       0       0       0       0   \n",
       "334465       0       0       0       0       0       0       0       0   \n",
       "...        ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "338036       0       0       0       0       0       0       0       0   \n",
       "338037       0       0       0       0       0       0       0       0   \n",
       "338038       0       0       0       0       0       0       0       0   \n",
       "338039       0       0       0       0       0       0       0       0   \n",
       "338040       0       0       0       0       0       0       1       0   \n",
       "\n",
       "        size_factor_neuted  \n",
       "334461            0.859205  \n",
       "334462            2.911020  \n",
       "334463           -1.323925  \n",
       "334464           -0.699192  \n",
       "334465            0.033776  \n",
       "...                    ...  \n",
       "338036           -1.274328  \n",
       "338037            2.346924  \n",
       "338038           -0.001917  \n",
       "338039           -0.563470  \n",
       "338040           -0.675732  \n",
       "\n",
       "[3580 rows x 41 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_trading_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "105f018e",
   "metadata": {},
   "source": [
    "我们以市值普遍较大的银行业和公司数量较多的化工行业为例，来分析一下其市值因子被中性化前后的变化。<br>\n",
    "其中银行业的申万一级行业代码为480000，化工行业代码为220000。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "63fd5d68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 银行\n",
    "sub_trading_data.query(\"ind_code == 480000 \")[['size_3sigma_std', 'size_factor_neuted']].hist(bins=100, figsize=(18 ,9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d32aef7b",
   "metadata": {},
   "source": [
    "银行业市值因子被中性化前后的分布图形状没有任何变化，但是对应的横坐标轴的数值发了改变"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "4643a7f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "size_3sigma_std       2.27\n",
       "size_factor_neuted    0.00\n",
       "dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_trading_data.query(\"ind_code == 480000 \")[['size_3sigma_std', 'size_factor_neuted']].mean().round(2)\n",
    "# size_3sigma_std       2.27\n",
    "# size_factor_neuted   -0.00"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc47137b",
   "metadata": {},
   "source": [
    "在被中性化前，银行业市值因子的均值达到了接近2.27的地步，这也证实了之前所说的银行业的上市公司市值普遍较大的情况。<br>\n",
    "而被中性化之后的市值因子均值几乎就是0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "0f20efb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMWzNgqKqXV9V9VfWuJff9SFXdU1Vvn/5ceZZ9r6iqO6vqrqo6PM+JAwDMSn8DAPO3njMYbkpyxQr3/3R3P3H6c/PylVV1XpKXJnlakkuTPKuqLh2ZLADAnNwU/Q0AzNWaAUN335rkIzMc+/Ikd3X3+7r7M0mOJHnmDMcBAJgr/Q0AzN/IZzA8v6reOT3F8OErrL8wyQeWLN89vQ8AYLvS3wDAjKq7196oan+S13X3E6bL+5J8KEkn+b+SPLq7/8myfb4lyVO7+9uny89Jcnl3f/dZxrg2ybVJsm/fvicdOXJkxbmcPHkye/fuXc9jYwVr1e+Oe+4/Y/myC8/f7Cltq/HX4vdvjPrNTu3GLKp+hw4dur27D2z5wKzLZvc36+1tznVb8fxcZH+xmWN7bRijfmPUb8xOrt9q/c2eWQ7Y3feevl1VP5/kdStsdneSxyxZvijJiVWOeWOSG5PkwIEDffDgwRW3O3bsWM62jrWtVb9rDh89Y/n4s8++7WZY9Phr8fs3Rv1mp3Zj1I/1mHd/s97e5ly3Fc/PRfYXmzm2v21j1G+M+o3ZrfWb6RKJqnr0ksW/n+RdK2z2B0kurqrHVdUDk1yd5DWzjAcAsNn0NwAwZs0zGKrqVUkOJnlEVd2d5IeTHKyqJ2ZyCuHxJN8x3faCJL/Q3Vd296mqen6SNyY5L8nLu/vdm/IoAAA2QH8DAPO3ZsDQ3c9a4e5fPMu2J5JcuWT55iSf8xVPAACLpL8BgPkb+RYJAAAAgCQCBgAAAGAOBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADD9ix6Amxv+w8fPWP5+PVXLWgmAADzsbS/0dsAzI8zGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhawYMVfXyqrqvqt615L6frKr3VtU7q+rVVfWws+x7vKruqKq3V9Vt85w4AMCs9DcAMH/rOYPhpiRXLLvvliRP6O4vS/LfkvzAKvsf6u4ndveB2aYIADB3N0V/AwBztWbA0N23JvnIsvve1N2npotvS3LRJswNAGBT6G8AYP6qu9feqGp/ktd19xNWWPfaJP+uu1+xwrr3J/lokk7yc9194ypjXJvk2iTZt2/fk44cObLididPnszevXvXnDMrW6t+d9xz/6r7X3bh+fOe0qrjb/Z4G+X3b4z6zU7txiyqfocOHbrdO9zb12b3N+vtbc51W/H8XK2/2cm9jdeGMeo3Rv3G7OT6rdbf7Bk5cFW9MMmpJK88yyZf090nquqLk9xSVe+dvmPwOaYvzjcmyYEDB/rgwYMrHvDYsWM52zrWtlb9rjl8dNX9jz/77PvOw/LxN3u8jfL7N0b9Zqd2Y9SPjZhXf7Pe3uZctxXPz9X6m53c2/jbNkb9xqjfmN1av5m/RaKqvi3J05M8u89yGkR3n5j+974kr05y+azjAQBsNv0NAMxupoChqq5I8v1Jvqm7P3WWbR5SVQ89fTvJU5K8a6VtAQAWTX8DAGPW8zWVr0ry1iSXVNXdVfW8JC9J8tBMTgt8e1XdMN32gqq6ebrrviRvqap3JPn9JEe7+w2b8igAADZAfwMA87fmZzB097NWuPsXz7LtiSRXTm+/L8mXD80OAGAT6G8AYP5m/gwGAAAAgNMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwbM+iJ8Dm2n/46BnLN13xkAXNBABgPpb3N8evv2pBMwFgKWcwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADFszYKiql1fVfVX1riX3fWFV3VJVfzT978PPsu8VVXVnVd1VVYfnOXEAgFnpbwBg/tZzBsNNSa5Ydt/hJL/T3Rcn+Z3p8hmq6rwkL03ytCSXJnlWVV06NFsAgPm4KfobAJirNQOG7r41yUeW3f3MJL88vf3LSf7eCrtenuSu7n5fd38myZHpfgAAC6W/AYD5q+5ee6Oq/Ule191PmC5/rLsftmT9R7v74cv2+eYkV3T3t0+Xn5PkK7v7+WcZ49ok1ybJvn37nnTkyJEV53Ly5Mns3bt37UdGkuSOe+4/Y/lx55+3av2Wb7/cZReeP5d5LWq8USO/f8sf63Z7bFvB83d2ajdmUfU7dOjQ7d19YMsHZl02u79Zb29zrpvl+bnR19TV+o2d3Ntsh9eGndzfbIf67WTqN2Yn12+1/mbPJo5bK9x31jSju29McmOSHDhwoA8ePLjidseOHcvZ1vG5rjl89Izlm654yKr1W779csefffZ9Z7HV440a+f1b/li322PbCp6/s1O7MerHHK27v1lvb3Oum+X5udHX1NX6jZ3c22yHv207ub/ZDvXbydRvzG6t36zfInFvVT06Sab/vW+Fbe5O8pglyxclOTHjeAAAm01/AwADZg0YXpPk26a3vy3Jb62wzR8kubiqHldVD0xy9XQ/AIDtSH8DAAPW8zWVr0ry1iSXVNXdVfW8JNcn+caq+qMk3zhdTlVdUFU3J0l3n0ry/CRvTPKeJL/e3e/enIcBALB++hsAmL81P4Ohu591llVPXmHbE0muXLJ8c5KbZ54dAMAm0N8AwPzNeokEAAAAwF8RMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMGzPoifA1rrjnvtzzeGjf7V8/PqrtnT8/UvG3mn2Hz6a6y479Vf12+raAQArW95fbOVr9E7ubZLF1g7YfZzBAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAMAEDAAAAMEzAAAAAAAzbs+gJsFj7Dx8d2v749VdtaP1m2s5zAwC2zkb6m+3eP2z3+QEs5QwGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYTMHDFV1SVW9fcnPx6vqe5dtc7Cq7l+yzQ+NTxkAYHPobwBgdntm3bG770zyxCSpqvOS3JPk1Sts+ubufvqs4wAAbBX9DQDMbl6XSDw5yR9395/M6XgAAIumvwGADZhXwHB1kledZd1XV9U7qur1VfX4OY0HALDZ9DcAsAHV3WMHqHpgkhNJHt/d9y5b9wVJ/rK7T1bVlUn+bXdffJbjXJvk2iTZt2/fk44cObLieCdPnszevXuH5nwuueOe+89Y3vfg5N5Pz+/4l114/qrjrbV+o8dfzUbH3sixT++/tH6z7D8y/m7g+Ts7tRuzqPodOnTo9u4+sOUDM2we/c16e5tz3SzPz432ExuxnXqbtcY/efJk3n//Zzft+Fux/yJ5bR2jfmN2cv1W62/mETA8M8l3dfdT1rHt8SQHuvtDq2134MCBvu2221Zcd+zYsRw8eHCGmZ6b9h8+esbydZedyovvmPmjNz7H8euvWnW8tdZv9Pir2ejYGzn26f2X1m+W/UfG3w08f2endmMWVb+qEjDsUPPub1brbc51szw/N9pPbMR26m3WGv/YsWO55g2f3LTjb8X+i+S1dYz6jdnJ9Vutv5nHJRLPyllOH6yqR1VVTW9fPh3vw3MYEwBgM+lvAGCDht7KrqrPT/KNSb5jyX3fmSTdfUOSb07yT6vqVJJPJ7m6R0+ZAADYRPobAJjNUMDQ3Z9K8kXL7rthye2XJHnJyBgAAFtJfwMAs5nXt0gAAAAA5zABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAw/YsegLnuv2Hj56xfPz6q+Z6vM221nij89nKxzP6bzHvf0sA2Kl2cn+zm3qblcbT3wCbyRkMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAwwQMAAAAwDABAwAAADBMwAAAAAAMEzAAAAAAw/YsegLnmv2Hj25o/fHrr9rM6exqG631VvNvDcBuob/ZOktred1lp7K8ndffAIvkDAYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGDYUMFTV8aq6o6reXlW3rbC+qupnququqnpnVX3FyHgAAJtNfwMAs9kzh2Mc6u4PnWXd05JcPP35yiQvm/4XAGA7098AwAZt9iUSz0zyKz3xtiQPq6pHb/KYAACbSX8DACuo7p5956r3J/lokk7yc91947L1r0tyfXe/Zbr8O0m+v7tXOt3w2iTXJsm+ffuedOTIkRXHPHnyZPbu3TvznBftjnvu39D2l114/lyPv+/Byb2f3tAhz1nLa3/HPfefUb+V1q+1/0bG26i1xt9qK81npz9/F0ntxiyqfocOHbq9uw9s+cAMmVd/s97eZjcY6W/W8/zc6PHPFbP0daP9y27qbzb62rDdeq1F05uM2cn1W62/Gb1E4mu6+0RVfXGSW6rqvd1965L1tcI+KyYa0xfvG5PkwIEDffDgwRUHPHbsWM62bie45vDRDW1//NkH53r86y47lRffMY8rY3a/5bW/5vDRM+q30vq19t/IeBu11vhbbaX57PTn7yKp3Rj1Y4Pm0t+st7fZDUb6m/U8Pzd6/HPFLH3daP+ym/qbjb42bLdea9G8to7ZrfUbukSiu09M/3tfklcnuXzZJncnecyS5YuSnBgZEwBgM+lvAGA2M7mLQuUAAAwESURBVAcMVfWQqnro6dtJnpLkXcs2e02Sb51+2vJXJbm/uz8482wBADaR/gYAZjdyrvy+JK+uqtPH+bXufkNVfWeSdPcNSW5OcmWSu5J8Kslzx6YLALCp9DcAMKOZA4bufl+SL1/h/huW3O4k3zXrGAAAW0l/AwCz2+yvqQQAAADOAQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACG7Vn0BNiY/YePnrF8/PqrFjST3W95rTe6ftE2+3dl9PGPzm8j+681V88jgMXS32wd/c3Gjj+y72b2Nittv5znEYvgDAYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABg2J5FT4DV7T98dGg9i7PRf5vl2x+//qp5TgcAto2lr3nXXXYqy1tS/c32pb8BVuMMBgAAAGCYgAEAAAAYJmAAAAAAhgkYAAAAgGECBgAAAGCYgAEAAAAYJmAAAAAAhgkYAAAAgGECBgAAAGDYzAFDVT2mqn63qt5TVe+uqu9ZYZuDVXV/Vb19+vNDY9MFANg8+hsAmN2egX1PJbmuu/+wqh6a5PaquqW7/+uy7d7c3U8fGAcAYKvobwBgRjOfwdDdH+zuP5ze/kSS9yS5cF4TAwDYavobAJhddff4Qar2J7k1yRO6++NL7j+Y5DeT3J3kRJJ/0d3vPssxrk1ybZLs27fvSUeOHFlxrJMnT2bv3r3Dc16UO+65f6Hj73twcu+nFzqFHW0r63fZhedvaPu1frc2erzR8VYaf+nzd/n+o493tf23ujabYaf/7Vu0RdXv0KFDt3f3gS0fmLkY7W/W29vsBiP9jd5kdjuxdtupv1nptWEjv8vLx97K3mal7Zfb7P5GbzJmJ9dvtf5mOGCoqr1Jfi/Jj3f3f1i27guS/GV3n6yqK5P82+6+eK1jHjhwoG+77bYV1x07diwHDx4cmvMi7T98dKHjX3fZqbz4jpErY85tW1m/49dftaHt1/rd2ujxRsdbafylz9/l+48+3tX23+rabIad/rdv0RZVv6oSMOxQ8+5vVuttdoOR/kZvMrudWLvt1N+s9Nqwkd/l5WNvZW+z0vbLbXZ/ozcZs5Prt1p/M/QtElX1gEwS/Fcuf/FNku7+eHefnN6+OckDquoRI2MCAGwm/Q0AzGbkWyQqyS8meU93/+uzbPOo6Xapqsun43141jEBADaT/gYAZjdyTtXXJHlOkjuq6u3T+16Q5EuSpLtvSPLNSf5pVZ1K8ukkV/c8PvQBAGBz6G8AYEYzBwzd/ZYktcY2L0nyklnHAADYSvobAJjd0GcwAAAAACQCBgAAAGAOBAwAAADAMAEDAAAAMEzAAAAAAAwTMAAAAADDBAwAAADAsD2LnsBOt//w0VXXH7/+qi2aCbvNZv9uLT/+8uOttX6W8a677FSuOcvjmvd4IzZ7LtvpsZ7r/FvAyvQ3bJbt1N9cd9mpHJzjWBudy1bT35w7Fvlv4QwGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYJiAAQAAABgmYAAAAACGCRgAAACAYQIGAAAAYNieRU9gs+0/fPSM5ePXXzXX4817e1ivef8ujq6ft9Hx5jnftf6OjP6dmfffqVFb/Xg2e/vV9oWdSn/DbrWb+5vt1NusdDz9zfz23creZqX9F8kZDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMAwAQMAAAAwTMAAAAAADBMwAAAAAMMEDAAAAMCwoYChqq6oqjur6q6qOrzC+qqqn5muf2dVfcXIeAAAm01/AwCzmTlgqKrzkrw0ydOSXJrkWVV16bLNnpbk4unPtUleNut4AACbTX8DALMbOYPh8iR3dff7uvszSY4keeaybZ6Z5Fd64m1JHlZVjx4YEwBgM+lvAGBGIwHDhUk+sGT57ul9G90GAGC70N8AwIyqu2fbsepbkjy1u799uvycJJd393cv2eZokn/V3W+ZLv9Oku/r7ttXON61mZxmmCSXJLnzLEM/IsmHZpo0ifqNUr8x6jc7tRuzqPo9trsfuYBxmdE8+5sN9DbnOn/fZqd2Y9RvjPqN2cn1O2t/s2fgoHcnecyS5YuSnJhhmyRJd9+Y5Ma1Bq2q27r7wMamymnqN0b9xqjf7NRujPqxAXPrb9bb25zrPD9np3Zj1G+M+o3ZrfUbuUTiD5JcXFWPq6oHJrk6yWuWbfOaJN86/bTlr0pyf3d/cGBMAIDNpL8BgBnNfAZDd5+qqucneWOS85K8vLvfXVXfOV1/Q5Kbk1yZ5K4kn0ry3PEpAwBsDv0NAMxu5BKJdPfNmbzILr3vhiW3O8l3jYyxAqcajlG/Meo3Rv1mp3Zj1I91W1B/cy7z/Jyd2o1RvzHqN2ZX1m/mD3kEAAAAOG3kMxgAAAAAkuzQgKGqfrKq3ltV76yqV1fVwxY9p52kqr6lqt5dVX9ZVbvuk0s3Q1VdUVV3VtVdVXV40fPZaarq5VV1X1W9a9Fz2Wmq6jFV9btV9Z7p8/Z7Fj2nnaSq/kZV/X5VvWNavx9d9JyAM+lLZqM3mZ2+ZIzeZHbnQl+yIwOGJLckeUJ3f1mS/5bkBxY8n53mXUn+QZJbFz2RnaCqzkvy0iRPS3JpkmdV1aWLndWOc1OSKxY9iR3qVJLruvvvJPmqJN/l929D/jzJ13f3lyd5YpIrpp/6D2wf+pIN0psMuyn6khF6k9nt+r5kRwYM3f2m7j41XXxbJt8/zTp193u6+85Fz2MHuTzJXd39vu7+TJIjSZ654DntKN19a5KPLHoeO1F3f7C7/3B6+xNJ3pPkwsXOaufoiZPTxQdMf3z4EGwj+pKZ6E0G6EvG6E1mdy70JTsyYFjmnyR5/aInwa52YZIPLFm+O/6IsgBVtT/J/5Tk/1vsTHaWqjqvqt6e5L4kt3S3+gE7nd6EbUFvsnG7vS8Z+prKzVRVv53kUSusemF3/9Z0mxdmcorOK7dybjvBeurHutUK9+2qpJHtr6r2JvnNJN/b3R9f9Hx2ku7+bJInTj+v59VV9YTudt0tbCF9ydzpTVg4vclsdntfsm0Dhu7+htXWV9W3JXl6kie379r8HGvVjw25O8ljlixflOTEgubCOaiqHpDJC/gru/s/LHo+O1V3f6yqjmVy3e2ueSGHnUBfMnd6ExZKbzJut/YlO/ISiaq6Isn3J/mm7v7UoufDrvcHSS6uqsdV1QOTXJ3kNQueE+eIqqokv5jkPd39rxc9n52mqh55+puGqurBSb4hyXsXOyuAYXoTFkZvMrtzoS/ZkQFDkpckeWiSW6rq7VV1w6IntJNU1d+vqruTfHWSo1X1xkXPaTubfqDo85O8MZMPsfn17n73Yme1s1TVq5K8NcklVXV3VT1v0XPaQb4myXOSfP30793bq+rKRU9qB3l0kt+tqndm0pDf0t2vW/CcgCX0JRunNxmjLxmmN5ndru9LytUFAAAAwKidegYDAAAAsI0IGAAAAIBhAgYAAABgmIABAAAAGCZgAAAAAIYJGAAAAIBhAgYAAABgmIABAAAAGPb/A3FzBM8cbBXSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_trading_data.query(\"ind_code == 220000 \")[['size_3sigma_std', 'size_factor_neuted']].hist(bins=100, figsize=(18 ,9))\n",
    "sub_trading_data.query(\"ind_code == 220000 \")[['size_3sigma_std', 'size_factor_neuted']].mean().round(2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "75b7f344",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "size_3sigma_std      -0.22\n",
       "size_factor_neuted    0.00\n",
       "dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_trading_data.query(\"ind_code == 220000 \")[['size_3sigma_std', 'size_factor_neuted']].mean().round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4804a0a",
   "metadata": {},
   "source": [
    "在被中性化前，化工行业的市值因子的均值极小，在-0.22左右。<br>\n",
    "从中也可以看出，当我们把化工行业的市值和银行业的市值放在一起比较的时候，是极不合理的。<br>\n",
    "在被中性化之后，化工行业市值因子的均值也几乎是0。<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71535d76",
   "metadata": {},
   "source": [
    "行情数据中的日期是交易当天的日期，例如2019年5月27日的因子需要在收盘后才能通过计算获得，<br>\n",
    "实际使用这些数据需要等到下一个交易日，也就是2019年5月28日。<br>\n",
    "为了避免使用未来信息，就需要将因子数据的时间进行调整<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "e3588010",
   "metadata": {},
   "outputs": [],
   "source": [
    "size_factor_df = sub_trading_data[['data_date', 'secucode', 'size_3sigma_std', 'size_factor_neuted']]\n",
    "size_factor_df['data_date'] = pd.to_datetime('2019-05-28')\n",
    "size_factor_df.columns = ['factor_date', 'secucode', 'size', 'size_factor_neuted']\n",
    "size_factor_df.to_csv('size.csv')"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "39b49021",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4acb13ff",
   "metadata": {},
   "source": [
    "均值法<br>\n",
    "1、将股票按照行业进行分组，计算每个行业分组的因子行业均值<br>\n",
    "2、将每个股票的因子值减去对应的行业的因子的均值，得到的差值：该因子在行业中性化后的中性值。<br>\n",
    "$$\n",
    "\\varepsilon=Y-\\bar{Y}_{\\text {Industry }_{i}}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08440c13",
   "metadata": {},
   "source": [
    "总结<br>\n",
    "  1. 去极值和异常值<br>\n",
    "  2. 标准化，相当于将因子变为一个分数<br>\n",
    "  3. 中性化，去除不同行业的影响，让因子可以“同台竞技”<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1f30c72f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d62cd8be",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82f99586",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
